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| | PO-GeP-M-1 : 2D to 3D Line Pattern Match (3DLM) Scheme in 6D for Marker Based Image Guided Radiation Therapy H.Kuo*, D.Lovelock, A.Damato, M.Zelefsky, S.Lin, C.Della-Biancia, S.Berry, M.Hunt |
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| | PO-GeP-M-2 : 3D Pelvic CT-MR Deformable Registration Using Unsupervised Cycle-Consistent FCN Y.Guo, X.Wu, Z.Wang, X.Pei, X.Xu* |
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| | PO-GeP-M-3 : 4DCT Quality Assurance with Multi-Vendors Respiratory Signals Input T.Lin*, A.Galuza, J.Liu, C.Ma |
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| | PO-GeP-M-4 : 90Y-Microspheres Radioembolization for Selective Internal Radiation Therapy in NGHA, Saudi Arabia , Statistics and Dosimetry N.SENHOU*, S.Alshehri |
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| | PO-GeP-M-5 : A Comparison of Internal Target Volumes (ITVs) Between 4DCT Simulation Images and 4DCBCT Pre-Treatment Images Using a Respiratory Phantom at Two Different Simulated Respiratory Rates S.Parker*, C.Whiddon, D.Nelson, J.Foster |
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| | PO-GeP-M-6 : A Comprehensive Deep Learning Model for the Tracking of Alzheimers Disease A.Deatsch*, M.Namías, R.Jeraj |
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| | PO-GeP-M-7 : A Comprehensive Evaluation of Deep Learning Design for Synthetic CT Generation S.Olberg*, J.Chun, B.Choi, I.Park, H.Kim, J.Kim, S.Mutic, O.Green, J.Park |
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| | PO-GeP-M-8 : A Data-Driven Analytical Framework to Track and Improve Clinical Workflow in Radiation Oncology R.Munbodh*, K.Leonard, T.Roth, M.Schwer, J.Brindle, E.Klein |
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| | PO-GeP-M-9 : A Deep Learning Method for Prediction of 3D Dose Distribution in Clinical Case S.Ahn*, E.Kim, K.Kim, C.Kim, S.Lee, Y.Lim, H.Kim, D.Shin, J.Jeong |
|
| | PO-GeP-M-10 : A Deep Learning-Based Interactive Software Tool to Assist Physicians Revising CTV Contours to Achieve Balanced Tumor Coverage and Organ Sparing A.Balagopal*, D.Nguyen, m.mashayekhi, M.Lin, A.Garant, N.Desai, R.Hannan, Y.Weng, X.Gu, S.Jiang |
|
| | PO-GeP-M-11 : A Deep Neural Network Approach for Enhancing Signal-To-Noise Ratio of MV EPID Images M.Ahmed*, H.Nourzadeh, J.Siebers |
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| | PO-GeP-M-12 : A Deep Reinforcement Learning Based Neural Network for Beam Orientation Selection Problem in the Treatment Planning of the IMRT Prostate Cancer A.Sadeghnejad Barkousaraie*, G.Bohara, S.Jiang, D.Nguyen |
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| | PO-GeP-M-13 : A Deep Transfer Learning-Based Radiomics Model for Prediction of Local Recurrence in Laryngeal Cancer Y.Jia*, X.Qi, J.Du, R.Chin, E.McKenzie, K.Sheng |
|
| | PO-GeP-M-14 : A Feasibility Study On the Development of a Deep Learning-Based Whole Brain Irradiation Automated Dose Calculation Algorithm A.Jaffe*, J.Keller |
|
| | PO-GeP-M-15 : A Framework for Iso-Toxic Adaptive Replanning Using Biophysical Models P.Prior*, X.Chen, X.Li |
|
| | PO-GeP-M-16 : A Framework to Evaluate Synthetic CTs Generated for First AI-Driven Online Adaptive Radiotherapy A.Quinn*, J.Kipritidis, D.Jayamanne, J.Booth |
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| | PO-GeP-M-17 : A Hierarchical 3D U-Net for Brain Tumor Substructure Segmentation J.Yang, R.Wang, Y.Weng*, L.Chen, Z.Zhou |
|
| | PO-GeP-M-18 : A Machine Learning Based Fully Automatic Magnification Calculation Method for Hip DR Photography Y.Jia*, H.Wang, X.Jin, H.Du, W.Chen, B.Yang |
|
| | PO-GeP-M-19 : A Machine Learning Model for Brain V12Gy/V60% Prediction of LINAC-Based Single-Iso-Multiple-Targets (SIMT) Stereotactic Radiosurgery (SRS): A Longitudinal Study X.Li*, J.Zhang, Y.Sheng, K.Lafata, N.Eclov, Y.Cui, W.Giles, J.Adamson, A.Rodrigues, Z.Wang, S.Yoo, F.Yin, Q.Wu, C.Wang |
|
| | PO-GeP-M-20 : A Method Based On Deep Convolution Network for Predicting Three-Dimensional Dose Distribution in Small Datasets of IMRT Nasopharyngeal Carcinoma F.Guo*, L.Dingjie |
|
| | PO-GeP-M-21 : A Method to Improve Organ Segmentation Between Medical Centers Using a Small Amount of Training Data K.Men*, J.Zhu, X.Chen, Y.Yang, J.Zhang, J.Yi, M.Chen, J.Dai |
|
| | PO-GeP-M-23 : A Multi-Observer Study Investigating the Effectiveness of Prostatic MpMRI to Dose Escalate Corresponding Histologic Lesions Using High Dose Rate Brachytherapy C.Smith*, D.Hoover, K.Surry, D.D'Souza, D.Cool, Z.Kassam, M.Bastian-jordan, J.Gomez, M.Moussa, J.Chin, S.Pautler, G.Bauman, A.Ward |
|
| | PO-GeP-M-24 : A Novel Coplanar Multi-Modality Tomographic Imaging for Image Guidance in Radiotherapy Using Hybrid Radiation Detector H.Gao*, Y.Xia |
|
| | PO-GeP-M-25 : A Novel Cost Function in AIF Model Fitting for DCE-MRI Studies R.He*, K.Wahid, B.McDonald, Y.Ding, A.Mohamed, B.Elgohari, K.Hutcheson, C.Fuller, S.Lai |
|
| | PO-GeP-M-26 : A Novel Method for Correcting CBCT Intensity Values and FOV Truncation S.Holler*, C.Guy, L.Padilla |
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| | PO-GeP-M-27 : A Novel Method for Dose-Of-The-Day Calculation for HN S.Holler*, C.Guy, L.Padilla |
|
| | PO-GeP-M-28 : A Novel Method to Automate the Optimization of Multileaf Collimator Transmission and Dosimetric Leaf Gap Parameters for Eclipse Treatment Planning System D.DiCostanzo*, A.Ayan |
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| | PO-GeP-M-29 : A Novel Methodology for Deriving Set-Up Margins Using Dose Accumulation and Bidirectional Local Distance A.Frederick*, S.Quirk, S.Weppler, M.Roumeliotis |
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| | PO-GeP-M-30 : A Novel Semi-Supervised Learning Method Using Soft-Label for Lung Segmentation On CT J.Zhou*, Z.Yan, Y.Zhang, N.Yue |
|
| | PO-GeP-M-31 : A Novel Software Tool for the Standardization of Structures and Dose Constraints to Facilitate a More Efficient Clinical Workflow M.Wagar*, L.Padilla, L.Yuan |
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| | PO-GeP-M-32 : A Novel, Rigid Phantom for Comprehensive End-To-End Verification of Adaptive Radiotherapy Systems A.Dare*, M.Price, A.Yock |
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| | PO-GeP-M-33 : A Patient-Specific Deep-Self-Supervised High-Resolution Method for CT Imaging Y.Lei, Y.Fu, T.Wang, W.Curran, T.Liu, X.Yang* |
|
| | PO-GeP-M-34 : A Patient-Specific Model for Collision Prediction Using An Azure Kinect Z.Simpson*, N.Sperling |
|
| | PO-GeP-M-35 : A Patient-Specific Model for Tracking Lung Tumor During Radiotherapy Using Surrogate Signal S.Fakhraei*, D.Sterling, E.Ehler, P.Alaei |
|
| | PO-GeP-M-36 : A Pilot Study for Using Non-Heating Volunteer Experiments as a Surrogate for In-Patient MR Thermometry Reproducibility During MR Hyperthermia I.Ribeiro*, S.Curto, M.Franckena, G.Van Rhoon, M.Paulides |
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| | PO-GeP-M-37 : A Practical Method to Automatically Delineate Gas Regions for MR-Guided Online Adaptive Radiotherapy of Abdominal Tumors E.Ahunbay*, X.Li |
|
| | PO-GeP-M-38 : A Simple Statistical Method to Reduce the Number of Patient-Specific QA Measurements for MR-Linac Adaptive Fractions A.Kim*, M.Ruschin, C.Mccann, P.Au, A.Singh, A.Sahgal, B.Keller |
|
| | PO-GeP-M-39 : A Study of Using Modulation Complexity Score as a Clinical Decision Aid for VMAT-Based Pancreas SBRT Treatment Planning Y.Zlateva*, X.Li, F.Yin, Q.Wu, C.Wang |
|
| | PO-GeP-M-40 : A Variable-OAR Volumetric Dose Prediction Model for Radiation Therapy Using Deep Learning m.mashayekhi*, I.Tapia, A.Sadeghnejad Barkousaraie, A.Balagopal, X.Zhong, S.Jiang, D.Nguyen |
|
| | PO-GeP-M-42 : Abdominal Synthetic CT Reconstruction Using Intensity Projection Prior for MRI-Only Adaptive Radiotherapy S.Olberg*, J.Chun, B.Choi, I.Park, H.Kim, T.Kim, J.Kim, O.Green, J.Park |
|
| | PO-GeP-M-43 : Accuracy of a Novel Facial Feature Point Algorithm for Head Motion Tracking Using Surface Guided Imaging to Remove the Mask in Head and Neck Radiotherapy Y.Ben Bouchta*, C.Cheng, K.Makhija, J.Sykes, E.Steiner, P.Keall |
|
| | PO-GeP-M-44 : Accuracy of the 3D Reference Coordinate Definition with G-Frame for Gamma Knife ICON L.Claps*, D.Mathew, Y.Watanabe |
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| | PO-GeP-M-45 : Accurate Tracking of Position and Dose During VMAT Based On VMAT-CT X.Zhao*, R.Zhang |
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| | PO-GeP-M-46 : Adaptive Treatment Replanning with a Commercial Field-In-Field Optimization Platform C.Matrosic*, K.Paradis (Younge), M.Matuszak |
|
| | PO-GeP-M-47 : Advantages of Spectral Energy CT Data for Deep Learning Applications A.Chatterjee*, M.Vallieres, J.Seuntjens, R.Forghani |
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| | PO-GeP-M-49 : ALARA in a Flash - Radiation Shielding and Safety Implications Following Linac Conversion to An Electron FLASH-RT Unit Y.Poirier*, S.Becker, S.Mossahebi, N.Lamichhane, A.Sawant |
|
| | PO-GeP-M-50 : Alert System for Monitoring Changes in Patient Anatomy During Radiation Therapy of Head and Neck Cancer B.Schaly*, J.Kempe, V.Venkatesan, S.Mitchell, J.Chen |
|
| | PO-GeP-M-51 : Alternative Methods to BMI for Obesity Related Setup Error Stratification of Abdominal Radiation Therapy Patients R.Price*, S.Lloyd, G.Nelson, B.Salter |
|
| | PO-GeP-M-52 : An AI-Based Tumor Auto-Contouring Algorithm for Non-Invasive Intra-Fractional Tumor-Tracked Radiotherapy (nifteRT) On Linac-MR J.Yun*, E.Yip, Z.Gabos, N.Usmani, D.Yee, K.Wachowicz, B.Fallone |
|
| | PO-GeP-M-53 : An Automated Contouring Workflow for Increased Standardization and Efficiency D.Hoffman*, J.Meyers, R.Manger, D.Hoopes, I.Dragojevic |
|
| | PO-GeP-M-54 : An Automatic Tumor Motion Determination Towards Daily ITV Margin Verification in Lung SBRT Using Markerless 4D-CBCT T.Fuangrod* |
|
| | PO-GeP-M-55 : An Automation Application to Analyze MLC Efficiency Using Real-Time Log Data for An Elekta-VersaHD Linear Accelerator B.Kassahun, |
|
| | PO-GeP-M-56 : An IGRT Safety Check: Automated T12 Vertebra Detection in CT and CBCT Y.Xie*, G.Sharp, D.Gierga, T.Hong, T.Bortfeld, K.Kang |
|
| | PO-GeP-M-57 : An NLP-Based Collaborative Intelligence Tool to Support Precision Medicine S.Dieterich*, P.Arora, S.Azghadi |
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| | PO-GeP-M-58 : An Optimized Training Module for Deep Learning-Based Auto-Segmentation A.Amjad*, W.Xhang, Z.Chen, Q.Zhou, T.Plautz, L.Buchanan, X.Li |
|
| | PO-GeP-M-59 : Analysis of Couch Shifts for Each Field for Proton Treatment Delivery of Head and Neck Cancer Patients: Towards Optimal Imaging Frequency N.Biswal*, D.Rodrigues, W.Yao, S.Chen |
|
| | PO-GeP-M-60 : Analysis of Patient Treatment Time for Adaptive Work Flows On the Elekta Unity D.Dunkerley*, S.Yaddanapudi, J.Snyder, D.Hyer, J.St-Aubin |
|
| | PO-GeP-M-61 : Analysis of Varian RPM Reproducibility During Deep Inspiration Breath Hold with AlignRT Monitoring E.Wright*, K.Bota, S.Karnas, S.Gaede |
|
| | PO-GeP-M-62 : Anonymization of DICOM Files in HTML5 Based Web Browser for Radiation Therapy P.Rana, W.Sleeman*, M.Poblacion, J.Palta, P.Ghosh, R.Kapoor |
|
| | PO-GeP-M-63 : Application of Kilovoltage Cone-Beam CT Images in Extracting Radiomics Signature for Predicting Radiation-Induced Pneumonitis Y.Huang*, H.Liu, R.Yu, Y.Pu, Y.Zhang |
|
| | PO-GeP-M-64 : Application of Multiparametric MRI Strategically Acquired Gradient Echo (STAGE) Imaging for Radiotherapy Planning E.Florez*, J.Storrs, R.Hamidi, A.Fatemi |
|
| | PO-GeP-M-65 : ArcCHECK for Machine Commissioning and Patient Specific QA: Which Phantom Should Be Used? Y.Tian*, K.Zhang, K.Men, J.Dai |
|
| | PO-GeP-M-66 : Architecture, Implementation, and Performance of An Automatic and High-Throughput Treatment Planning Service: The Radiation Planning Assistant L.Zhang*, C.Cardenas, D.Rhee, C.Nguyen, A.Olanrewaju, L.Court |
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| | PO-GeP-M-67 : Are Sub-Region Radiomic Features From Pre-Treatment FDG-PET-CT Biomarkers of Recurrence for Cervical Cancer? I.Vergalasova*, K.Nie, Y.Li, T.Cui, B.Liu, M.Sayan, M.Reyhan, N.Yue, L.Hathout |
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| | PO-GeP-M-68 : Assessing the Dosimetric Links Between Organ-At-Risk Delineation Variability and Treatment Planning Variability W.Choi, V.Leandro Alves*, H.Nourzadeh, E.Aliotta, J.Siebers |
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| | PO-GeP-M-69 : Assessment of Bone Electron Density Effects On Dose Calculation and Optimization Accuracy for MRI-Only Treatment Planning for Cervical Carcinoma in 1.5 T MR-Linac S.Ding*, H.Liu, Y.Li, B.Wang, B.Liu, X.Qi, X.Cao, X.HUANG |
|
| | PO-GeP-M-70 : Assessment of CBCT-Based Dose Accumulation for Robustly Optimized Intensity-Modulated Proton Therapy Plans with Different Uncertainty Scenarios for Treatment of Prostate Cancer Y.Xu*, M.Butkus, N.Brovold, A.King, T.Diwanji, A.Pollack, M.Abramowitz, N.Dogan |
|
| | PO-GeP-M-71 : Assessment of Intrafraction Motion Based On Intraprostatic Fiducials During VMAT Delivery R.Tolakanahalli*, S.Davis |
|
| | PO-GeP-M-72 : Assessment of Need for MR Guidance in Adaptive RT A.Sethi*, E.Omari, J.Ingram, K.Stoeckigt, T.Thomas, J.Roeske, T.Refaat, R.Wynn |
|
| | PO-GeP-M-73 : Assessment of Ventilation-Perfusion (V/Q) Relationships with 68Ga V/Q PET/CT in Lung Cancer Patients Z.Li*, J.Callahan, M.Hofman, S.Siva, T.Yamamoto |
|
| | PO-GeP-M-74 : Auto-Determination of the Dextrous WorkSpace in Robotic Stereotactic Radiosurgery O.Ogunmolu*, X.Liu, R.Wiersma |
|
| | PO-GeP-M-75 : Automated Detection of Field Match Lines Between Supraclavicular and Tangent Irradiation Fields with Cherenkov Imaging R.Hachadorian*, C.Farwell, M.Jermyn, D.Gladstone, L.Jarvis, B.Pogue |
|
| | PO-GeP-M-76 : Automated Dose Accumulation for Online Adaptive Radiotherapy of Head and Neck Cancers S.Gros*, A.Santhanam, D.Elliott, J.Roeske, R.Patel, H.Kang |
|
| | PO-GeP-M-77 : Automated Fiducial Tracking During VMAT Using Beam's-Eye-View Images D.Ferguson*, T.Harris, M.Shi, M.Jacobson, I.Valencia Lozano, C.Williams, M.Myronakis, P.Huber, P.Baturin, R.Fueglistaller, D.Morf, M.Lehmann, R.Berbeco |
|
| | PO-GeP-M-78 : Automated Identification of DICOM-RT Structures Using Map Projections and Machine Learning D.Cutright*, T.Wu, A.Roy, M.Gopalakrishnan, B.Mittal |
|
| | PO-GeP-M-79 : Automatic Prostate Bed Target Segmentation On Daily Cone-Beam CT Image Using a Multi-Path 3D Dense-UNet J.Fu*, S.Yoon, A.Kishan, K.Singhrao, Z.Wang, J.Lewis, D.Ruan |
|
| | PO-GeP-M-80 : Automatic Segmentation of Prostate Bed in Post-Prostatectomy CT Images X.Xu*, C.Lian, D.Shen, J.Lian |
|
| | PO-GeP-M-81 : Automatic Segmentation of the Prostate On CT Images Using a Bi-Directional Convolutional LSTM U-Net with Novel Loss Function X.Li*, H.Bagher-Ebadian, C.Li, E.Mohamed, F.Siddiqui, B.Movsas, D.Zhu, I.Chetty |
|
| | PO-GeP-M-82 : Automatic Segmentation of the Trigeminal Nerve On MRI Using Deep Learning K.Mulford*, S.Ndoro, S.Moen, Y.Watanabe, P.Van De Moortele |
|
| | PO-GeP-M-83 : Automatic Tumor Segmentation in Digital Breast Tomosynthesis Using U-Net A.Qasem*, G.Qin, J.Wang, Z.Zhou |
|
| | PO-GeP-M-84 : Auto-Segmentation On Liver With U-Net And Pixel Deconvolutional U-Net H.Yao*, J.Chang |
|
| | PO-GeP-M-85 : Benchmarking the Plan Review Performance of a Commercial Automation Tool and a Dynamic Checklist Technology Using TG-275 High Risk Failure Modes J.Hoisak*, R.Manger, G.Kim, I.Dragojevic |
|
| | PO-GeP-M-86 : Building Workflow Automation of Radiotherapy Platform Via Data Lake Approach A.Li*, L.Cervino, M.Hunt, J.Mechalakos, L.Santanam, P.Zhang, J.Deasy |
|
| | PO-GeP-M-87 : Calculation of Rotational Patient Positional Error Corrected Setup Margin in Frameless Stereotactic Radiosurgery and Radiotherapy B.Sarkar* |
|
| | PO-GeP-M-88 : Can Deep Learning Raise the Quality of Low-Dose CT Images Above That of Normal-Dose CT Images? T.Bai*, D.Nguyen, G.Wang, S.Jiang |
|
| | PO-GeP-M-89 : Can Rectum Stability Issues Be Managed with IGRT in Prostate Radiotherapy? M.Rosu-Bubulac*, A.Ricco, A.Urdaneta, S.Kim, E.Weiss, J.Palta |
|
| | PO-GeP-M-90 : Can Surface-Guided Imaging Improve CT Image Quality? R.Shaw* |
|
| | PO-GeP-M-91 : CAPULET: A Novel Coded Aperture Prompt-Gamma Ultra-Light Imaging DETector A.Vella*, F.Van den Heuvel |
|
| | PO-GeP-M-92 : CBCT-Based Adaptive Intensity Modulated Proton Radiotherapy P.Sabouri, M.Mundis, S.Andersson, R.Nilsson, K.Eriksson, S.Chen, S.Mossahebi* |
|
| | PO-GeP-M-93 : Characterization of CT Hounsfield Units Uniformity of 3D-Printed Materials for Proton Therapy E.Orton*, C.Engelberts, R.Orbovic, M.Crocker, B.Basaric, D.Sobczak, L.Zhao |
|
| | PO-GeP-M-94 : Characterization of Patient Shifts From Ct Simulation to First Fraction to Improve Tumor Localization S.Drehmel*, C.Ferreira, J.Lawrence, E.Ehler |
|
| | PO-GeP-M-95 : Characterization of Spatial Properties of Dosimetric Data for Voxel-Based Analyses: Disentangling Contributions From Heart and Lung Substructures to Radiation Induced Toxicities R.Mohan*, S.Monti, A.Stanzione, T.Xu, M.Durante, G.Palma, Z.Liao, L.Cella |
|
| | PO-GeP-M-96 : Characterizing the Excursion of Sensitive Cardiac Substructures Due to Respiration C.Miller*, E.Morris, A.Ghanem, M.Pantelic, E.Walker, C.Glide-Hurst |
|
| | PO-GeP-M-97 : Classification of TI-RADS Class-4 Thyroid Nodules Based On Shape and Texture Features From Ultrasound Images Q.Meng*, T.Liu, W.Lu, L.Shi, J.Qiu, W.Lu |
|
| | PO-GeP-M-98 : Clinical Evaluation of Atlas and Deep Learning-Based Automatic Contouring of Multiple Organs at Risk and Clinical Target Volumes for Breast Cancer M.Choi*, B.Choi, S.Chung, N.Kim, J.Chun, Y.Kim, J.Chang, J.Kim |
|
| | PO-GeP-M-99 : Clinical Evaluation of Deep Learning and Atlas Based Auto-Contouring of Bladder and Rectum for Prostate Radiotherapy J.Zabel, J.Conway, A.Gladwish, J.Skliarenko, G.Didiodato, L.Goorts-matthews, A.Michalak, S.Reistetter, J.King, K.Malkoske, K.Nakonechny, M.Tran, N.McVicar* |
|
| | PO-GeP-M-100 : Clinical Evaluation of Two Orthogonal Radiographic Imaging Systems for Image-Guided Stereotactic Radiosurgery J.Duan*, G.Cui, F.Yin |
|
| | PO-GeP-M-101 : Clinical Utility of External and Internal Surrogates for Respiratory Motion Management in Pancreas SBRT A.Briggs*, B.Zwan, G.Angelis, M.Shepherd, A.Kneebone, G.Hruby, J.Booth |
|
| | PO-GeP-M-102 : Clinical Utility of Six Degrees of Freedom Patient Alignment in Non-Cranial Lesions C.Njeh*, H.Salmon, V.Goutsouliak |
|
| | PO-GeP-M-103 : Cluster Analysis On Longitudinal Data of Parkinson Disease Subjects M.Salmanpour*, A.Saberi, G.Hajianfar, M.Shamsaei, H.Soltanian-zadeh, A.Rahmim |
|
| | PO-GeP-M-104 : CNN Based Organ Segmentation On Chest Radiograph Using Synthetic X-Ray Image Reconstructed From MDCT S.Kim*, C.Ahn, C.Heo, J.Kim |
|
| | PO-GeP-M-105 : Combining Images and Clinical Diagnostic Information to Improve Automatic Segmentation of Nasopharyngeal Carcinoma Tumors On MR Images M.Cai*, Q.Yang, Y.Guo, Z.Zhang, J.Wang, W.Hu, C.Hu |
|
| | PO-GeP-M-106 : Comparing Delivered Dose Estimations with and Without Dose Recalculation for Head-And-Neck Adaptive Radiotherapy Y.Hu*, M.Aristophanous, L.Cervino, A.Caringi, N.Allgood, M.Hunt |
|
| | PO-GeP-M-107 : Comparing Fiducial Movement with Tumor Movement Using 4D-CT for Cyberknife Treatment of Lung Cancer Patients to Identify Where Fiducials Should Be Placed W.Belcher*, J.Jung, A.Ju |
|
| | PO-GeP-M-108 : Comparing the Stability of Deep Inspiration Breath-Holds Between ABC and VisionRT During Breast Irradiation Z.Iqbal, R.McBeth, M.Joo*, D.Parsons, A.Rahimi, N.Kim, A.Sawant, X.Gu, B.Zhao |
|
| | PO-GeP-M-109 : Comparison of Setup Error of Chestwall and Heart Using AlignRT-Guided Vs. RPM-Guided DIBH in Left Breast Radiotherapy W.Lu*, G.Li, L.Hong, E.Gillespie, E.Yorke, S.Berry, J.Mechalakos, S.Powell, X.Tang |
|
| | PO-GeP-M-110 : Comparison of Artificial Intelligence Based Decision Support Tool for Head and Neck Treatment Planning R.McBeth*, D.Nguyen, H.Wang, R.Norouzi-Kandalan, m.mashayekhi, X.Zhong, Z.Iqbal, A.Godley, S.Jiang, M.Lin |
|
| | PO-GeP-M-111 : Comparison of Cartesian 4 Fps Vs Radial 8 Fps On 0.35T MRI-Linac H.Gach*, T.Kim, B.Lewis, A.Price, A.Marko, D.Yang, S.Mutic, O.Green |
|
| | PO-GeP-M-112 : Comparison of Contour-Based, Image-Based, and Contour-Image-Based Deformable Image Registration for Adaptive Re-Planning K.Kainz*, H.Zhong, A.Tai, E.Ahunbay, X.Li |
|
| | PO-GeP-M-113 : Comparison of CT-MR Image Registrations of BrainLab Elements MBM SRS and Varian Eclipse J.Li*, Y.Yu, H.Liu |
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| | PO-GeP-M-114 : Comparison of Daily Plan Adaptation Strategies On a Cohort of Pancreatic Cancer Patients Treated with SBRT A.Magallon-Baro*, M.Milder, P.Granton, J.Nuyttens, M.Hoogeman |
|
| | PO-GeP-M-115 : Comparison of Proton Stopping Power Measurements of Animal Tissues From Proton CT and X-Ray CT Systems D.DeJongh*, E.DeJongh, V.Rykalin, M.Pankuch, B.Kreydick, J.Welsh, R.Schulte, N.Karonis, C.Ordonez, K.Duffin, J.Winans, G.Coutrakon, C.Sarosiek |
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| | PO-GeP-M-116 : Comparison of Surface Imaging and 2DkV Imaging Vs. CBCT in Left Breast DIBH Radiotherapy W.Lu*, N.Yamada, L.Hong, W.Choi, X.Tang, J.Mechalakos, S.Berry, P.Romesser, O.Cahlon, S.Powell, G.Li |
|
| | PO-GeP-M-117 : Comparison of Yttrium-90 Dosimetry of Single Energy Window and Dual Energy Window SPECT/CT Imaging Protocols L.Chen* |
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| | PO-GeP-M-118 : Completely Automatic Deformable Image Registration Pipeline Using Automatically Derived Segmentations and Deformation Vector Fields E.McKenzie*, N.Tong, R.Neph, Y.Jia, D.Ruan, K.Sheng |
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| | PO-GeP-M-119 : Compton Camera Event Classification Using Artificial Neural Networks P.Maggi*, C.Barajas, G.Kroiz, J.Basalyga, S.Peterson, D.Mackin, R.Panthi, S.Beddar, M.Gobbert, J.Polf |
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| | PO-GeP-M-120 : Cone-Beam CT Radiomics for Patients with Liver Tumors Treated by Stereotactic Body Radiation Therapy: A Pilot Study P.Yang*, J.Shan, Q.Zhou, L.Xu, Z.Cao, T.Niu, M.Huang, X.Sun |
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| | PO-GeP-M-121 : Construction of Computational Non-Human Primates Model for Radiation Dosimetry T.Xie* |
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| | PO-GeP-M-122 : Continuous On-Beam Computor Tomographic Image Reconstruction at the Moment of Treatment by Amplitude/phase Scaling of Deformation Vector Fields J.Jung*, I.Yeo, J.Kim, B.Yi |
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| | PO-GeP-M-123 : Convolutional Neural Network Learning From RT Dose Distribution and Images Improves Predicting Locoregional Recurrence for Head and Neck Cancer A.Wu*, Y.Li, M.Qi, X.Lu, Y.Liu, L.Zhou, T.Song |
|
| | PO-GeP-M-124 : Correlating Daily CBCT 3D Gamma Density with Daily Volumetric and Dosimetric Changes in Head and Neck Patients M.Sharma*, A.Witztum, J.Pan, J.Chan, T.Solberg, E.Hirata |
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| | PO-GeP-M-125 : Creation of An Automated Hand-Crafted Radiomics Methodology and Assessment of Its Potential to Contribute to a Prospective Trial E.Carver*, J.Snyder, D.Bergman, M.Shah, S.Siddiqui, N.Wen |
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| | PO-GeP-M-126 : CT Image Parameter Estimation Using PCA-Based Deep Learning in Chronic Obstructive Pulmonary Disease A.Moslemi*, W.Tan, J.Bourbeau, J.Hogg, H.Coxson, M.Kirby |
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| | PO-GeP-M-127 : CT Vs. Fluoroscopy Guidance for Nusinersen Intrathecal Injection: Quantitative Evaluation of the Learning Process Effect On Patients Radiation Exposure R.Al Helo*, L.Zimmermann, A.Azar, N.Bass, D.Jordan, N.Azar |
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| | PO-GeP-M-128 : CT-Radiomics May Predict Cardiac Toxicity After Radiation Therapy for Localized Breast Cancer in Women D.Toomeh*, J.Meshman, L.Wang, D.Kwon, I.Mihaylov, C.Takita |
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| | PO-GeP-M-129 : Daily Dosimetric Evaluation of the Delivery of High Precision Breast Irradiation Using Synthetic CTs Derived From CBCT Images H.Jung*, C.Guy, A.Urdaneta, D.Arthur, S.Kim, J.Palta, M.Rosu-Bubulac |
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| | PO-GeP-M-130 : Dark Field Proton Radiography: A Proof of Principle M.Freeman*, J.Allison, E.Aulwes, P.Magnelind, F.Mariam, J.Medina, W.Meijer, F.Merrill, L.Neukirch, T.Schurman, R.Sidebottom, Z.Tang, F.Trouw, D.Tupa, J.Tybo, M.Espy |
|
| | PO-GeP-M-131 : Data Collection for Radiation Oncology Big Data Initiatives: An Integrated Clinical Workflow Based Solution R.Kapoor*, W.Sleeman, J.Palta |
|
| | PO-GeP-M-132 : Deconvolution of Ionization Chamber-Measured Small Field Profiles Using a Neural Network A.Schönfeld*, G.Yan, H.Looe, B.Poppe |
|
| | PO-GeP-M-133 : Deep Learning Applied to Ultrasound Catheter Localization for HDR Prostate Brachytherapy: Evaluation of An Initial Model D.Liu*, S.Tupor, N.Leong, E.Sadikov, A.Amjad, S.Zilles |
|
| | PO-GeP-M-134 : Deep Learning Based Treatment Plan Evaluation X.Zhong*, D.Nguyen, R.McBeth, A.Balagopal, m.mashayekhi, M.Lin, S.Jiang |
|
| | PO-GeP-M-135 : Deep Learning for 3D Automated Delineation of Primary Gross Tumor Volume for Nasopharyngeal Carcinoma by CT Combining Contrast-Enhanced CT Z.Dai*, X.Wang, H.Jin, C.Cai, S.Zhao, Y.Zhu, Y.Chen |
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| | PO-GeP-M-136 : Deep Learning Prediction of Radiotherapy Treatment Machine Parameters L.Hibbard* |
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| | PO-GeP-M-137 : Deep Learning Segmentation of Cardiac Substructures in Breast Cancer Radiotherapy Patients X.Jin*, J.Hilliard, J.Dise, J.Kavanaugh, I.Zoberi, M.Thomas, C.Robinson, G.Hugo |
|
| | PO-GeP-M-138 : Deep Learning-Based Auto-Segmentation of OARs in Head and Neck CT Images Z.Shen*, A.Garsa, S.Sun, N.Bai, C.Zhang, A.Shiu, E.Chang, W.Yang |
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| | PO-GeP-M-139 : Deep Proton DoseNet: A Deep Neural Network for Proton Dose Distribution Image Super-Resolution Y.Nomura*, T.Matsuura, H.Shirato, S.Shimizu, L.Xing |
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| | PO-GeP-M-140 : Deep-Learning Dose Prediction as First Step Toward Real-Time Adaptive Replanning L.Buchanan*, Z.Chen, W.Xhang, Q.Zhou, D.Schott, X.Li |
|
| | PO-GeP-M-141 : Deformable Image Registration of Diagnostical CT and Planning CT for Breast Conserving Radiotherapy X.Xie*, H.Yan, J.Dai |
|
| | PO-GeP-M-142 : Delay-Line Based Optical Reservoir Computing Towards Real-Time Respiratory Motion Prediction Z.Liang, C.Shi, X.Tang*, J.Li, X.Shen, Z.Huang |
|
| | PO-GeP-M-143 : Derivation of Photon Cross Section Coefficients of Virtual Monoenergetic CT Images for Radiotherapy Treatment Planning J.Harms*, C.Chang, S.Charyyev, J.Zhou, X.Yang, L.Lin |
|
| | PO-GeP-M-144 : Designing a Simple CNN Model in Terms of Size and Computational Complexity to Perform Classification Task On Medical Images R.Immanni, G.Valdes*, Y.Interian |
|
| | PO-GeP-M-145 : Detectability of MR Suitable Prostate Fiducial Markers in An Anthropomorphic Phantom Utilizing the TrueBeam Advanced Imaging Package During VMAT Prostate Treatment M.Klem*, K.Jones, J.Turian |
|
| | PO-GeP-M-146 : Detector Performance Effects On Compton Camera Data Quality P.Maggi*, S.Peterson, R.Panthi, D.Mackin, S.Beddar, J.Polf |
|
| | PO-GeP-M-147 : Determination of Planning Target Volume Margin for Gastric Lymphoma Radiotherapy Using Daily Four-Dimensional Cone-Beam Computed Tomography Y.Shimohigashi*, Y.Doi, Y.Kono, M.Maruyama, Y.Kai, R.Toya |
|
| | PO-GeP-M-148 : Development and Evaluation of a Fast Patient Alignment Tool Using Megavoltage-Topogram On Helical TomoTherapy: A Pooled Analysis X.Qi*, F.Chu, D.Low |
|
| | PO-GeP-M-149 : Development and Validation of a Machine Learning Predictive Model of IMRT Patient-Specific Quality Assurance Approval Using Gamma-Radiomics C.Yaly, J.Lizar, P.Santos, A.Colello Bruno, G.Viani, J.Pavoni* |
|
| | PO-GeP-M-150 : Development and Validation of a Web-Crawler-Based Medical Records Information Aggregation Tool H.Liu*, Y.Huang, Y.Pu, H.Wu, Y.Zhang |
|
| | PO-GeP-M-151 : Development of 4DCT-MR Based Numerical Lung Phantoms for 4D Radiotherapy and Imaging Investigations A.Duetschler*, M.Krieger, D.Weber, A.Lomax, Y.Zhang |
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| | PO-GeP-M-152 : Development of a Dose Accumulation Pipeline to Support MR-Guided Adaptive Radiation Therapy D.Rusu*, E.Morris, C.Glide-Hurst |
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| | PO-GeP-M-153 : Development of a No Action Level (NAL) Protocol for Physician Time Management During MRI Guided Online Standard Fractionation Adaptive Radiation Therapy for Head and Neck Cancer S.Vedam*, B.McDonald, J.Yang, P.Castillo, A.Sobremonte, B.Lee, N.Hughes, M.Mohammadsaid, J.Wang, S.Choi, C.Fuller |
|
| | PO-GeP-M-154 : Development of An Anthropomorphic Multimodal Abdominal 4D Phantom for MR-Guided Radiotherapy A.Weidner*, A.Runz, G.Echner |
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| | PO-GeP-M-155 : Dice Coefficient of Auto Segmentation and Its Implication On Inverse Prostate SBRT Treatment Planning C.Yan*, B.Guo, R.Tendulkar, P.Xia |
|
| | PO-GeP-M-156 : Differentiating the Pathological Subtypes of Primary Lung Cancer for Patients with Brain Metastases Based On Radiomics Features From Brain CT Images X.Jin*, Z.Ji, C.Xie |
|
| | PO-GeP-M-157 : Difficulty-Aware Meta-Learning for Rare Disease Diagnosis X.Li*, L.Yu, L.Xing |
|
| | PO-GeP-M-158 : Diffusion Parameters of Fornix in Multiple Sclerosis Patients with Memory Disturbance A.Mahjoub*, A.Omidi, M.Nezamzadeh, S.Raminfard, M.Moghadasi |
|
| | PO-GeP-M-159 : Direct Dose Calculation On CBCTs for Various Treatment Sites in Adaptive Radiotherapy C.Wessels*, S.Scheib |
|
| | PO-GeP-M-160 : Direct Tumor Visualization in 0.35T MRgRT for Tumor Motion Control in Free Breathing T.Kim*, B.Lewis, A.Price, T.Mazur, H.Gach, J.Park, B.Cai, E.Wittland, L.Henke, H.Kim, S.Mutic, O.Green |
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| | PO-GeP-M-161 : Does Daily MRI-Guided Online Re-Planning in Prostate SBRT Improve Dosimetry Compared to Isocenter Shift Adaptation? M.Ruschin*, B.Keller, J.Detsky, A.Loblaw, J.Stewart, M.Campbell, A.Kim, K.Wong, M.Davidson, M.Wronski, D.Vesprini, C.Mccann |
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| | PO-GeP-M-162 : Does the Choice of Deep Learning Architecture Matter? Experience From a Radiotherapy Case Study S.Gay*, A.Jhingran, B.Anderson, L.Zhang, D.Rhee, C.Nguyen, T.Netherton, J.Yang, K.Brock, H.Simonds, A.Klopp, B.Beadle, K.Kisling, L.Court, C.Cardenas |
|
| | PO-GeP-M-163 : Domain Classification and Analysis of National Institutes of Health Funded Medical Physics Research M.Scarpelli*, B.Whelan, K.Farahani |
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| | PO-GeP-M-164 : Dose Deformation for Adaptive Planning Using Varian's SmartAdapt J.Vickress*, A.Rangel, H.Afsharpour |
|
| | PO-GeP-M-165 : Dose Prediction and Customized Optimization Settings by Learning From Previous Cases: Application to SBRT Treatment Planning E.Schreibmann* |
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| | PO-GeP-M-166 : Dose to Circulating Blood in VMAT TBI Using a Dynamic Whole Body Blood Model B.Guo* |
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| | PO-GeP-M-167 : Dose Verification of Four-Dimensional Cone-Beam Computed Tomography for Target Localization of Planned and Unplanned Target Motion C.Baley*, S.Stathakis, P.Myers, N.Kirby, K.Rasmussen, N.Papanikolaou, D.Saenz |
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| | PO-GeP-M-168 : Dosimetric Analysis of Automated Treatment Planning for Whole Brain Radiotherapy with A Deep Learning Approach E.Han*, C.Cardenas, C.Nguyen, T.Briere, j.Li, D.Yeboa, C.Wang, L.Court, M.Martel, Z.Wen |
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| | PO-GeP-M-169 : Dosimetric Analysis of OARnet Auto-Delineations for Head and Neck Organs-At-Risk M.Soomro*, H.Nourzadeh, V.Leandro Alves, W.Choi, J.Siebers |
|
| | PO-GeP-M-170 : Dosimetric and Geometric Evaluation of Five Commercial Contour Propagation Tools for Online Adaptive Radiotherapy D.Nash*, S.Juneja, A.Mcwilliam, A.Palmer, E.Vasquez Osorio |
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| | PO-GeP-M-171 : Dosimetric Comparison of CT Compatible Plastic Cones to Traditional Metal Cones for IntraOp Radiation Therapy S.Jain*, A.Steinmann, J.Woollard, N.Gupta, A.Ayan |
|
| | PO-GeP-M-172 : Dosimetric Effects of a Novel Concept of Adaptive Radiotherapy for Prostate Cancer Patients M.Splinter*, T.Bostel, P.haering, C.Lang, N.Nicolay |
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| | PO-GeP-M-173 : Dosimetric Evaluation of Online Adaptive Planning for Patients with Glioblastoma Multiforme Cancer with MRI at Two Week Intervals D.To*, M.Liu, I.Xhaferllari, D.Lack, P.Chinnaiyan, D.Yan |
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| | PO-GeP-M-174 : Dosimetric Impact of Magnetic Resonance Imaging Distortion in Photon and Proton Treatment Plans Y.Yan*, J.Yang, F.Pirlepesov, Y.Ding, J.Uh, L.Zhao, T.Merchant, J.Wang, C.Hua |
|
| | PO-GeP-M-175 : Dosimetric Planning Comparison for Left-Sided Breast Cancer Radiotherapy: 4DCT Vs Deep-Inspiration Breath-Hold O.Chau*, H.Fakir, M.Lock, R.Dinniwell, F.Perera, A.Erickson, S.Gaede |
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| | PO-GeP-M-176 : Dosimetric Results for Magnetic Resonance Guided Radiotherapy Using Hybrid Magnetic Resonance/Computed Tomography Compatible Phantom M.Kim*, S.Lee, B.Choe, T.Suh |
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| | PO-GeP-M-177 : Dosimetric Variation Between Manual Contouring and Auto-Segmentation for Normal Structures in Intensity Modulated Radiotherapy C.Alekchander*, V.Kaliyaperumal, S.Chawla, A.Agarwal, S.Goel, A.Sharma |
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| | PO-GeP-M-178 : Dynamic HU Mapping and Deformable Image Registration Algorithm for Adaptive Treatment Planning and Dose Calculation Using Neural Network S.John Edward Selvin*, T.Santosh, M.Kather Hussain, P.Ravindran |
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| | PO-GeP-M-179 : Effect of Field Number and Beam Angle On ERE for Lung Cancers Radiotherapy Planning in 1.5 T MR-Linac S.Ding*, H.Liu, B.Wang, Y.Li, Y.XIA, X.HUANG |
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| | PO-GeP-M-180 : Effect of Using Harmonized Radiomic Features On Predicting Volume of Radiographic Changes Following Stereotactic Body Radiotherapy in Lung R.Mahon*, M.Ghita, G.Hugo, N.Kalman, N.Mukhopadhyay, E.Weiss |
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| | PO-GeP-M-181 : Effectiveness of Simple Data Imputation for Missing Feature Values in Binary Classification A.Chatterjee*, H.Woodruff, M.Lobbes, Y.Van Wijk, M.Beuque, J.Seuntjens, P.Lambin |
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| | PO-GeP-M-182 : Efficiency of Integrated Real-Time Monitored Liver SBRT with Deep-Expiration-Breath-Hold S.Shen*, R.Jacob, C.Schneider, R.Popple, X.Wu, J.Fiveash |
|
| | PO-GeP-M-183 : Efficient Acquisition of MR-Linac Commissioning Data Using Cherenkov Projection Imaging D.Alexander*, R.Zhang, P.Bruza, B.Pogue, D.Gladstone |
|
| | PO-GeP-M-184 : Enabling Jaw Tracking in Monitoring of Prostate Motion Using On Board MVKV Imaging System L.Happersett*, A.Damato, P.Wang, P.Zhang |
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| | PO-GeP-M-186 : End-To-End Testing of Adaptive Radiotherapy in the Elekta MR-Linac Utilising 3d Printed Phantoms A.Axford*, N.Dikaios, C.Clark, D.Roberts, P.Evans |
|
| | PO-GeP-M-187 : Establishing a Routine Clinical Dose Verification Workflow Utilizing CBCT Imaging and Log Files G.Kuzmin*, P.Xia, P.Qi |
|
| | PO-GeP-M-188 : Establishment and Validation of a Multi-Omics Nomogram to Predict Lymph Node Metastasis of Esophageal Squamous Cell Carcinoma Z.Li, B.Li* |
|
| | PO-GeP-M-189 : Estimation of Radiation Dose to Korean Population by Cardiovascular SPECT-CT Examinations Y.Yun, H.Nam, W.Kim, K.Kim* |
|
| | PO-GeP-M-191 : Evaluating Daily Cone Beam CT Gamma Index as a Parameter for Decision Making in Adaptive Radiation Therapy Programs M.Bakhtiari* |
|
| | PO-GeP-M-192 : Evaluating ICBCT Image Quality at Halcyon Linac for Patient Set Up Verification M.Gei*, J.Visak, D.Pokhrel |
|
| | PO-GeP-M-193 : Evaluating the Accuracy of Atlas-Based Auto-Segmentation for Pediatric Craniospinal Irradiation S.Al-ward*, O.Ates, M.Gargone, T.Merchant, L.Zhao |
|
| | PO-GeP-M-194 : Evaluating the Clinical Utility of Cherenkov Imaging in Radiotherapy R.Hachadorian, D.Alexander, I.Tendler, M.Jermyn, B.Pogue*, L.Jarvis |
|
| | PO-GeP-M-195 : Evaluating the Efficacy of Regression Models in Radiomics: A Study with NSCLC Patients H.Choi* |
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| | PO-GeP-M-196 : Evaluating the Performance of a Generative Adversarial Network-Based (GAN-Based) Architecture for Automatic Detection of Fiducial Markers in Prostate MRI-Only Radiotherapy Images K.Singhrao*, J.Fu, D.Ruan, A.Mikaeilian, N.Parikh, A.Kishan, J.Lewis |
|
| | PO-GeP-M-197 : Evaluation of a Novel Automated Treatment Planning Tool for Cervical Cancer in IMRT J.Guo*, J.Zhou, L.Chen, J.Ni, Y.Xu, G.Gan, W.Gon, C.Ma, Y.Li, W.Zhan, X.Xu, S.Qin |
|
| | PO-GeP-M-198 : Evaluation of An Artificial Intelligence (AI) Based Auto Contouring Workflow Box for Head and Neck Radiotherapy L.Zhuang*, M.Pankuch, E.Bowers, M.Posner |
|
| | PO-GeP-M-199 : Evaluation of Deep Learning-Based Auto-Segmentation of Target Volume and Normal Organs in Breast Cancer Patients S.Chung*, J.Chang, Y.Chang, B.Choi, J.Chun, J.Kim, Y.Kim |
|
| | PO-GeP-M-200 : Evaluation of Intrafractional Motion in Spine Stereotactic Body Radiotherapy M.Kanda*, Y.Nakajima, K.Ito, Y.Suda, H.Ogawa, K.Abe, K.Karasawa |
|
| | PO-GeP-M-201 : Evaluation of Liver Motion in Real Time Using Diaphragm Tracking Versus Tracking Implanted Gold Markers for Stereotactic Ablative Radiation Therapy (SAbR) N.Hassan Rezaeian* |
|
| | PO-GeP-M-202 : Evaluation of Machine Learning Algorithms for Treatment Planning Parameter Calculation J.Chow*, R.Jiang, F.Ng |
|
| | PO-GeP-M-203 : Evaluation of Markers for Catheter Detection in MRI-Guided Gynecological Brachytherapy E.Kaza*, R.Cormack, I.Buzurovic |
|
| | PO-GeP-M-204 : Evaluation of MRI Radiomics Feature Robustness Using a Virtual Radiomics Phantom C.Ma*, X.Wang, K.Qing, N.Yue, K.Nie |
|
| | PO-GeP-M-205 : Evaluation of Nanoparticle Uptake by Cervical and Liver Cancer Cell Lines for Enhanced Radiation Therapy S.David*, T.Gray, D.Patel, J.Valesquez, N.Bassiri, K.Mayer, N.Kirby |
|
| | PO-GeP-M-206 : Evaluation of Real-Time Cine Imaging During MLC and Gantry Motion for MR-Guided Radiation Therapy J.Kielbasa*, S.Meeks, P.Kelly, T.Willoughby, O.Zeidan, A.Shah |
|
| | PO-GeP-M-207 : Evaluation of Simple MR-Based Online Adaptive Radiotherapy for Prostate Cancer I.Xhaferllari*, D.Lack, R.Levitin, D.To, M.Liu, J.Liang, D.Krauss, D.Yan |
|
| | PO-GeP-M-208 : Evaluation of Surface Registration Accuracy for Patient Positioning in Head and Neck Radiotherapy Using Normal Distribution Transform Algorithm S.Fakhraei*, C.Wilke, P.Alaei |
|
| | PO-GeP-M-209 : Evaluation of Synthetic CT Generation Technique Using An Anthropomorphic Multi-Modality (CT/MRI) Pelvic Phantom for MRgRT H.Jin*, S.Lee, H.An, J.Park, C.Choi, E.Chie, H.Kim, H.Kim, J.Kim |
|
| | PO-GeP-M-210 : Evaluation of T2-Weighted MRI Pulse Sequences for Visualization and Sparing of Urethra with MR-Guided Radiation Therapy (MRgRT) On-Board MRI J.Pham*, R.Savjani, Y.Gao, M.Cao, P.Hu, D.Low, M.Steinberg, A.Kishan, Y.Yang |
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| | PO-GeP-M-211 : Evaluation of the Accuracy of Deformable Image Registration On the TomoTherapy Treatment Planning System Y.Nakajima*, R.Suganami, S.Hashimoto, H.Ogawa, N.Kadoya, K.Karasawa |
|
| | PO-GeP-M-212 : Evaluation of the Direct Density Algorithm for Energy-Independent Radiotherapy Planning A.Shutler*, A.Sarkar, G.Grousset, J.Shah, F.Mourtada |
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| | PO-GeP-M-213 : Evaluation of the Protective Effect of Nano-Composites Reinforced with Cerium-Oxide Nanoparticles Against Diagnostic X-Ray N.Riyahi-Alam*, s.salimi, N.Riyahi Alam, R.Zohdiaghdam, M.Mahmoudian |
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| | PO-GeP-M-214 : Evaluation of the Relationship Between Positioning Accuracy and Scanning Volume Using Optical Surface Scanning System and Surface Image Features H.Kojima*, A.Takemura, S.Ueda, K.Noto, H.Yokoyama, H.Adachi, S.Takamatsu |
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| | PO-GeP-M-215 : Evaluation of the Stability of Radiomics Features Using 4D-CT and Across Radiomics Platforms for Lung and Liver Tumors X.Wang*, C.Ma, h.wang, Y.Zhang, N.Yue, K.Nie |
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| | PO-GeP-M-216 : Expanded Visual Guidance of Breath-Hold for CBCT-Guided Online Adaptive Radiotherapy (ART) in a Closed-Bore Configuration T.Kim, J.Shin*, J.Kim, E.Barberi, L.Henke, S.Mutic, B.Cai |
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| | PO-GeP-M-217 : Expanding Global Radiotherapy Access by Adopting Hypofractionated Radiotherapy and Combination Immunotherapy for Breast and Prostate Cancer W.Swanson*, O.Irabor, J.Wirtz, S.Yasmin-Karim, W.Ngwa |
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| | PO-GeP-M-218 : Feasibility of An Assisted Chart Review for Assessing the Development of Radiation Pneumonitis J.Mckenzie*, J.Wu, H.Shen, S.Rajapakshe, R.Rajapakshe, A.Lin |
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| | PO-GeP-M-219 : Feasibility of Direct Proton Dose Calculation On CBCT Scans in Esophageal Cancer G.Defraene*, M.Thomas, R.De Roover, S.Michiels, T.Depuydt, E.Sterpin, K.Haustermans |
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| | PO-GeP-M-220 : Feasibility of Knowledge-Based Planning to Improve Online Adaptive Stereotactic Body Radiation Therapy for Hepatocellular Carcinoma K.Dess*, J.Dow, K.Paradis (Younge), J.Burmeister, M.Matuszak |
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| | PO-GeP-M-221 : Feasibility of MRI-Only Treatment Planning for Stereotactic Body Radiation Therapy (SBRT) for Prostate Cancer R.Nosrati*, W.Lam, M.Paudel, A.Pejovic-Milic, G.Morton, G.Stanisz |
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| | PO-GeP-M-222 : Feasibility of Pseudo 4pi Approach for Stereotactic Radiosurgery On a Linear Accelerator with On-Board MRI E.Omari*, I.Rusu |
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| | PO-GeP-M-224 : Feasibility of Surface Tracking During Framed Stereotactic Radiosurgery A.Paxton*, V.Sarkar, H.Zhao, C.Dial, B.Salter |
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| | PO-GeP-M-225 : Feasibility of Using Surface Guided Deep Inspiration Breath Hold (DIBH) in Conjunction with CBCT for Target Localization for Radiation Therapy H.Zhao*, A.Paxton, V.Sarkar, Y.Huang, F.Su, G.Stinnett, P.Rassiah-Szegedi, M.Szegedi, R.Price, X.Li, C.Dial, J.Kunz, G.Nelson, B.Salter |
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| | PO-GeP-M-226 : Feasibility Study of a Curved Flexible Probe for Abdominal Imaging During Radiation Therapy J.Zhou*, X.Huang, H.Endou, K.Sasaki, H.Hooshangnejad , D.Han, K.Ding |
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| | PO-GeP-M-227 : Four-Dimensional Cone-Beam CT Imaging Using Displacement Vector Fields Extracted From Deformable Image Registration: Phantom Study N.Alsbou*, S.Ahmad, I.Ali |
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| | PO-GeP-M-228 : Functional Programming and Immutable Data in Treatment Planning Systems N.Depauw*, T.Madden, H.Kooy |
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| | PO-GeP-M-229 : Gadolinium Neutron Capture Agent for Charged Particle Radiotherapy K.Van Delinder*, R.Khan, J.Grafe |
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| | PO-GeP-M-230 : Gadolinium Neutron Capture Therapy Using FDA-Approved MRI Contrast Agents W.Swanson*, S.Yasmin-Karim, V.Ainsworth, N.Bih, R.Mueller, E.Sajo, W.Ngwa, M.Jandel |
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| | PO-GeP-M-231 : Generalizability Issue of Deep Learning Models in Medicine and Its Potential Solutions: Illustrated with CBCT to CT Image Conversion X.Liang*, D.Nguyen, S.Jiang |
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| | PO-GeP-M-232 : Generating Synthetic CT From Daily Cone Beam CT Using Machine Learning Models S.Yoganathan, S.Paloor*, R.Hammoud, N.Hammadi |
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| | PO-GeP-M-233 : Generation of Pseudo MR From CT for Soft-Tissue Sarcoma Using SRCycle GAN X.Meng*, C.Wang, X.Wu, X.Xu, X.Xu, X.Pei |
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| | PO-GeP-M-234 : GTV Autosegmentation for Palliative Head and Neck Radiotherapy S.Gay*, C.Cardenas, C.Nguyen, T.Netherton, A.Aggarwal, K.Naidoo, H.Simonds, B.Beadle, L.Court |
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| | PO-GeP-M-235 : Head Neck Cancer Locoregional Recurrence Prediction Using Delta-Radiomics Feature K.Wang*, Z.Zhou, L.Chen, R.Wang, D.Sher, J.Wang |
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| | PO-GeP-M-236 : High Resolution Spectroscopic MRI and Scripting: Towards Automated Planning for a Multi-Center Clinical Trial E.Schreibmann, K.Ramesh*, H.Shu, H.Shim |
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| | PO-GeP-M-237 : Higher Ventilation Induced Radiation Pneumonitis for Non-Small Cell Lung Cancer Patients T.Lin*, S.Kumar, A.Dayal, C.Ma |
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| | PO-GeP-M-238 : How Low Can You Go? A CBCT Dose Reduction Study A.Olch*, P.Alaei |
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| | PO-GeP-M-239 : Identifying Robust Radiomic Features Extracted From Images Generated by 0.35T MR-Linac R.Ericsson-szecsenyi*, G.Zhang, G.Redler, K.Latifi, V.Feygelman, M.Tomaszewski, E.Moros |
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| | PO-GeP-M-240 : Impact of Changes in Body Shapes On Radiation Therapy Dose Distribution After Uterine Cervical Cancer Surgery M.Sasaki*, H.Ikushima, K.Kitagawa, Y.Kano, M.Tominaga, H.Honda, W.Sugimoto, M.Oita |
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| | PO-GeP-M-241 : Impact of Deep Learning Based Image Quality Augmentation On CBCT Based Radiomics Analysis M.Huang*, Z.Zhang, J.Lee, Z.Jiang, T.Niu, F.Yin, L.Ren |
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| | PO-GeP-M-242 : Impact of Gantry, MLC, and Patient Table Power On An MRgRT System B.Lewis*, B.Gu, R.Klett, R.Lotey, O.Green, T.Kim |
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| | PO-GeP-M-243 : Impact of ICBCT Reconstruction On Cone Beam Acquisitions G.Stinnett*, G.Nelson, R.Price, H.Zhao, A.Paxton, V.Sarkar, B.Salter |
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| | PO-GeP-M-244 : Impact of Image Reconstruction Kernel On CT Number to Proton Stopping Power Calibration M.Chacko*, H.Grewal, S.Rana, D.Wu, J.Sonnad |
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| | PO-GeP-M-245 : Impact of Imaging Frequency On the Accuracy of Patient Treatment Dose: An Evaluation Based On Halcyon MVCBCT H.Wang*, Q.Hu, Y.Huang, Y.Zhang |
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| | PO-GeP-M-246 : Impact of Partial Volume Effect From Air in Pulmonary 18F-FDG PET as An Imaging Biomarker for Pulmonary Toxicity After Radiotherapy L.Sensoy*, M.Daly, T.Yamamoto |
|
| | PO-GeP-M-247 : Impact of Resistance On Treatment Failure in Metastatic Prostate Cancer Patients M.Turk*, D.Valentinuzzi, A.Roth, R.Jeraj |
|
| | PO-GeP-M-248 : Impact of Respiratory Motion Management with Patient Biofeedback On Diffusion Weighted Imaging of Liver Cancer Patients Pre- and Post-SBRT B.Lewis, S.Kim, T.Kim* |
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| | PO-GeP-M-249 : Implantable Cardioverter Defibrillator Lead Tip as a Surrogate Fiducial for Non-Invasive Cardiac Radioablation in the Treatment of Ventricular Tachycardia P.Samson*, D.Anand, S.Goddu, M.Prusator, D.Yang, N.Knutson, J.Park, P.Cuculich, C.Robinson, G.Hugo |
|
| | PO-GeP-M-250 : Implementation of Intelligent Dynamic Checklists to Improve Treatment Planning and Physics Plan Review J.Hoisak*, R.Manger, I.Dragojevic |
|
| | PO-GeP-M-251 : Implications of Cervix-Influencing Organs Variation During Online Adapted Radiation Treatments M.Ahmed*, A.Yock, N.Newman, D.Ayala-peacock, A.Chakravarthy, M.Price |
|
| | PO-GeP-M-252 : Improved Auto-Segmentation for CT Male Pelvis: Comparison of Deep Learning to Traditional Atlas Segmentation Methods C.Halley*, H.Wan, A.Kruzer, D.Pittock, D.Darkow, M.Butler, N.Cole, M.Bending, P.Jacobs, A.Nelson |
|
| | PO-GeP-M-253 : Improvement of Real-Time Motion Tracking with Daily Optimized Registration of Cine MRI On MR-Linac T.Keiper*, A.Tai, X.Chen, E.Paulson, F.Lathuiliere, S.Beriault, F.Hebert, D.Cooper, M.Lachaine, X.Li |
|
| | PO-GeP-M-254 : Improving Accuracy of Predicted Lung Dosimetry in 90Y-Microsphere Radioembolization with 99mTc-MAA Planar Scintigraphy B.Lopez*, A.Mahvash, J.Long, M.Lam, S.Kappadath |
|
| | PO-GeP-M-255 : Improving Automated OAR Segmentation for Gynecological Patients with Data From Prostate Cancer Patients Y.Yuan*, Y.Na, M.CHADHA, Y.Lo |
|
| | PO-GeP-M-256 : Increased DQE Through Use of Light Field Cameras and Thick Scintillators in Megavoltage Imaging B.Preusser*, E.Pearson, P.La Riviere, R.Wiersma |
|
| | PO-GeP-M-257 : Independent Feature Selection in Radiomics Cross-Validation Is Essential to Estimate the True Model Performance J.Du*, X.Qi, R.Chin, K.Sheng |
|
| | PO-GeP-M-258 : Individualized Prediction of Local Recurrence After Radical Surgery for Esophageal Squamous Cell Carcinoma: Development and Validation of Radiomics Nomogram Z.Li, B.Li* |
|
| | PO-GeP-M-259 : Individuals in the Prediabetes Stage Exhibit Reduced Hippocampus and Amygdala Subregion Volumes D.Cui, W.Cao, Q.Jiao, J.Qiu, Y.Guo* |
|
| | PO-GeP-M-260 : Influence of Respiratory Motion On Target Dose Verification in IMRT for Lung Cancer Radiotherapy H.Chen* |
|
| | PO-GeP-M-261 : Initial Experience in MRI-Based Brain Metastases Detection Using Deep Learning J.Teruel*, K.Bernstein, P.Galavis, K.Spuhler, J.Silverman, D.Kondziolka, K.Osterman |
|
| | PO-GeP-M-262 : Initial Investigation of Dose Calculation On Intra-Irradiation Cone-Beam CT Images H.Iramina*, M.Nakamura, T.Mizowaki |
|
| | PO-GeP-M-263 : Interactive Contouring Through Contextual Deep Learning M.Trimpl*, D.Boukerroui, E.Stride, K.Vallis, M.Gooding |
|
| | PO-GeP-M-264 : Intra-Fraction Correction for Frameless Stereotactic Treatment to Trigeminal Neuralgia Y.Huang*, B.Zhao, N.Wen, I.Chetty, S.Siddiqui |
|
| | PO-GeP-M-265 : Intrafraction Imaging: Simultaneous KV Image Acquisition During MV Treatment Delivery to Monitor Patient and Target Motion L.Sensoy, A.Hernandez, D.Hernandez, D.Campos, Y.Rong, S.Benedict*,
|
|
| | PO-GeP-M-266 : Intrafraction Motion Monitoring to Determine PTV Margins in Early Stage Breast Cancer Patients Receiving Neoadjuvant Partial Breast SABR M.Mouawad*, O.Lailey, M.O'neil, P.Poulsen, P.Keall, H.Biernaski, M.Brackstone, M.Lock, B.Yaremko, S.Karnas, A.Kornecki, O.Shmuilovich, G.Muscedere, I.Nachum, F.Prato, R.Thompson, N.Gelman, S.Gaede |
|
| | PO-GeP-M-267 : Intra-Fraction Motion Pattern Assessed Using Principal Component Analysis for Frameless Stereotactic Radiosurgery T.Cui*, X.Wang, I.Vergalasova, Y.Zhang, N.Yue, K.Nie |
|
| | PO-GeP-M-268 : Introducing MRI Guidance Into Skin Brachytherapy T.Harris*, D.O'Farrell, I.Buzurovic, S.Friesen, P.Devlin |
|
| | PO-GeP-M-269 : Investigating Internal-External Motion Correlation Using Fast Helical Free-Breathing CT and Simultaneous Respiratory Bellows M.Lauria*, R.Navaratna, D.O'Connell, P.Lee, D.Low |
|
| | PO-GeP-M-270 : Investigating Stability and Reproducibility of Deep Inspiration Breath Hold for Liver Stereotactic Body Radiotherapy D.Parsons*, Z.Iqbal, N.Sanford, R.Reynolds, S.Stojadinovic, T.Aguilera, T.Chiu, W.Lu, M.Folkert, X.Gu |
|
| | PO-GeP-M-271 : Investigating the Impact of Secondaries Neutrons On Compton Camera for Medical Imaging S.Peterson*, P.Maggi, R.Panthi, D.Mackin, S.Beddar, J.Polf |
|
| | PO-GeP-M-272 : Investigation of Carbon Ion Radiation Therapy Range Uncertainties Via Prompt Gamma Rays Monitoring P.Galanakou*, T.Leventouri, W.Muhammad |
|
| | PO-GeP-M-273 : Investigation of Partial-Arc CBCT Protocols for Imaging Extremities P.Watson*, E.Poon |
|
| | PO-GeP-M-274 : Investigation of Radiomics Modelling Discriminability of Tumor Subvolumes in Predicting Distant Metastasis After Radiotherapy in Advanced Nasopharyngeal Carcinoma T.Yu*, X.Teng, S.Lam, J.Zhang, F.Lee, K.Au, W.Yip, J.Cai |
|
| | PO-GeP-M-275 : In-Vivo Measurement of Potassium in Mice Using Neutron Activation Analysis S.Tabbassum*, H.Nie |
|
| | PO-GeP-M-276 : Is a Tattooless Setup as Accurate as Tattoo Based Setup for Radiation Treatment? L.Huang*, E.Suarez, F.Gretah, R.Szwedowski, M.Naik, J.Greskovich, Z.Wang, T.Djemil |
|
| | PO-GeP-M-277 : Knowledge Discovery From Existing Radiotherapy Patient Databases Based On Unsupervised Learning Methodology D.Tewatia*, R.Tolakanahalli |
|
| | PO-GeP-M-278 : KV-Energy Fan-Beam CT Imaging Performance of a Novel Biology-Guided Radiotherapy (BgRT) Machine Z.Sun*, H.Gao, S.Xu, J.Ye, C.Huntzinger, S.Shirvani, S.Mazin, T.Laurence |
|
| | PO-GeP-M-279 : Large-Scale Multi-Patient Radiotherapy Data Mining Framework with Commercial Plan Reporting Tool M.Moazzezi*, K.Moore, K.Sysock, X.Ray, K.Kisling |
|
| | PO-GeP-M-280 : Learned Delineation of Gross Tumor Volume Incorporating Intra-Observer Variability T.Marin*, C.Ma, R.Lahoud, F.Xing, P.Wohlfahrt, M.Moteabbed, J.Woo, X.Ma, K.Grogg, Y.Chen, G.El Fakhri |
|
| | PO-GeP-M-281 : Learning Clinical Expertise Using Deep 3D Networks: An Automated Clinical Target Volume (CTV) Delineation for Non-Small Cell Lung Cancer (NSCLC) Patients Y.Xie*, K.Kang, Y.Wang, F.Keane, M.Khandekar, H.Willers, T.Bortfeld |
|
| | PO-GeP-M-282 : Lesion Insertion Tool to Assess PET-MR Attenuation Correction Methods: Matched Contralateral Uptake Lesion Insertions in Pelvis PET-MR Data Y.Natsuaki*, A.Leynes, K.Wangerin, M.Hamdi, A.Rajagopal, R.Laforest, P.Larson, T.Hope, S.St. James |
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| | PO-GeP-M-283 : Leveraging Incomplete Multimodal Biomarkers for Cancer Treatment Outcome Prediction M.Saad*, S.He, W.Thorstad, H.Gay, X.Wu, Y.Zhao, S.Ruan, X.Wang, H.Li |
|
| | PO-GeP-M-284 : Limitations of Dose-Volume Metrics in Deformable Registration: Implications for Organs-At-Risk in Sharp Dose Gradients H.Keller*, A.Mehlisch, P.Manser, M.Fix, K.Han, T.Tadic |
|
| | PO-GeP-M-285 : Long Term Stability of KV Cone Beam CT (CBCT) Image Quality Assurance for IBA Proteus PLUS Proton Therapy System J.George*, J.Bennouna, S.Rana, J.Yu, L.Coutinho, M.Hobson, L.Perles, S.George, A.Gutierrez |
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| | PO-GeP-M-286 : Longitudinal Analysis of Parotid Gland Anatomical Changes During Radiotherapy by Recurrent Convolutional Neural Networks D.Lee*, P.Zhang, S.Alam, J.Jiang, S.Nadeem, A.Caringi, N.Allgood, Y.Hu |
|
| | PO-GeP-M-287 : Longitudinal Change of T2 Map During MR-Guided SBRT for Pancreatic Cancer X.Chen*, H.Nasief, E.Paulson, E.Ahunbay, P.Prior, W.Hall, B.Erickson, X.Li |
|
| | PO-GeP-M-288 : Low Cost MRI Geometric Distortion Phantom Made From Paintballs and Pourable Foam B.Rasmussen*, X.Du, R.Milano |
|
| | PO-GeP-M-289 : Machine Learning Models in Predicting Pathological Complete Response After Neo-Adjuvant Chemoradiation for Locally Advanced Rectal Cancer Y.Zhang*, M.diMayorca, L.Shi, X.Sun, S.Jabbour, Y.Zhang, N.Yue, K.Nie |
|
| | PO-GeP-M-290 : Machine Learning of MAA SPECT Lung Perfusion Radiomics to Predict Radiation and Immune-Mediated Pneumonitis in Patients with Locally Advanced Non-Small Cell Lung Cancer H.Thomas T, J.Zeng, P.Kinahan, R.Miyaoka, H.Vesselle, R.Rengan, S.Bowen* |
|
| | PO-GeP-M-291 : Managing Cardiac Motion in Ventricular Tachycardia: Use of Deformable Registration to Determine Shifts Magnitude E.Schreibmann, D.Qian*, M.Lloyd, K.Higgins |
|
| | PO-GeP-M-292 : Markerless Motion Tracking with Treatment Beam Imaging in Spine SBRT Treatment: A Phantom Study T.Li*, F.Li, W.Cai, P.Zhang, M.Hunt, X.Li |
|
| | PO-GeP-M-293 : Mean Energy, Dose, and Sources of Out-Of-Field Radiation in Flattening-Filter and Flattening-Filter-Free 6 MV Beams, Measured with TL Dosimeters V.Lopez-guadalupe, A.Rodriguez Laguna, M.Poitevin-Chacon, E.Lopez-Pineda, M.Brandan* |
|
| | PO-GeP-M-294 : Metrological Analyses On Mismatches in Voxel-To-Voxel Image Comparisons A.Chu*, Q.Peng, M.Garg, W.Tomé |
|
| | PO-GeP-M-296 : Modeling of Human Body Tissue Compositions for Monte Carlo Algorithm of Proton Therapy Dose Computation with the Single Energy Computed Tomography Calibration Curve M.Ghasemi Ghonchehnazi*, G.Evans, C.Shang |
|
| | PO-GeP-M-297 : Monte Carlo Calculation of Radiation Exposure to Astronauts Using 4D Extended Cardiac-Torso (XCAT) Phantoms J.Houri*, P.Segars, A.Kapadia |
|
| | PO-GeP-M-298 : Monte Carlo Simulation Framework for Scatter Correction of KV and MV CBCT Images of the Varian TrueBeam STx Linac B.Zapien Campos*, A.Martinez Davalos, H.Alva, M.Rodriguez-Villafuert |
|
| | PO-GeP-M-299 : Motion of Electronic Portal Imaging Devices and Clinical Implications for Multi-Leaf Collimator Quality Assurance J.Nasehi Tehrani*, C.Kalavagunta, G.Lasio, S.Chen, B.Yi |
|
| | PO-GeP-M-300 : MRI Radiomic Analysis for Survival Prediction in Diffuse Midline Glioma L.Tam, M.Han, D.Yecies, K.Yeom, S.Mattonen* |
|
| | PO-GeP-M-301 : MRI Radiomics for Predicting a Poor Prognosis in Patients with GBM P.Borges, J.Lizar, G.Viani, J.Pavoni* |
|
| | PO-GeP-M-302 : MRI Visualization of Applicators for Skin HDR Brachytherapy E.Kaza*, R.Cormack, P.Devlin, I.Buzurovic |
|
| | PO-GeP-M-303 : MRI-Only Brain Radiotherapy: Assessing the Dosimetric Accuracy of Synthetic CT Images Generated Using Cycle GAN S.Kazemifar*, A.Barragan Montero, T.Bai, R.Timmerman, Y.Park, M.Lin, S.Jiang, A.Owrangi |
|
| | PO-GeP-M-304 : Multi-Modality Brain Tumor Segmentation Using a Modified Cascaded 3D U-Net for Imbalanced Classes W.Kong*, D.Li, Y.Yang |
|
| | PO-GeP-M-305 : Multi-Modality Imaging of Treatment Response After Stage III Non-Small Cell Lung Cancer Radiotherapy H.Young*, O.Chau, K.Burgers, T.Lee, F.Prato, G.Wisenberg, S.Gaede |
|
| | PO-GeP-M-306 : Multi-Modality Imaging Reduces Intra-Observer Variability in GTV Delineation of Sarcomas and Chordomas R.Lahoud*, T.Marin, M.Moteabbed, F.Xing, X.Ma, P.Wohlfahrt, N.Shusharina, J.Woo, K.Grogg, Y.Chen, C.Ma, G.El Fakhri |
|
| | PO-GeP-M-307 : Multiple Resolution Residual Network for Automatic Glioblastoma Segmentation in MRI H.Um*, J.Jiang, F.Tixier, R.Young, H.Veeraraghavan |
|
| | PO-GeP-M-308 : Multiple Resolution Residual Network for Automatic Thoracic Organs-At-Risk Segmentation in CT H.Um*, J.Jiang, M.Thor, A.Rimner, L.Luo, J.Deasy, H.Veeraraghavan |
|
| | PO-GeP-M-309 : Multi-Section CT Radiomics Can Accurately Predict Postoperative Recurrence in Esophageal Squamous Cell Cancer Patients Achieving PCR After Neoadjuvant Chemoradiotherapy Followed by Surgery Q.Qiu*, Y.Yin |
|
| | PO-GeP-M-310 : Normal Tissue and Tumor Segmentation Using V-Net Regularized by YOLO C.Hsu*, C.Morin, T.Kirby, M.Metzger, J.Flerlage, S.Kaste, M.Krasin, B.Shulkin, J.Lucas |
|
| | PO-GeP-M-311 : Offline Assessment and Adaptation of Prostate and Head-And-Neck Radiotherapy Using Velocity M.Hyun*, A.Smith, P.Patel, W.Nie, S.Wisnoskie |
|
| | PO-GeP-M-312 : On the Feasibility of Daily Delivered Dose Evaluation Using RTapp for Adaptive Lung SBRT Treatments N.Zulkarnain*, D.Mathew, C.Cho, A.Santhanam, D.Elliott, S.Seshan, Y.Watanabe |
|
| | PO-GeP-M-314 : On the Quantification of PET Images for Treatment of Lung Cancer Patients H.Zhong*, N.Morrow, J.Kim |
|
| | PO-GeP-M-315 : On the Relationship Between Hounsfield Unit and Electron Density: Learning to Be More Accurate A.Sudhyadhom*, J.Scholey, R.Marants, V.Kearney, M.Descovich, L.Vinas |
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| | PO-GeP-M-316 : Online Adaptive Planning Strategy for 1.5T MR-Linac J.Yang*, A.Sobremonte, S.Vedam, K.Brock, A.Ohrt, C.Fuller, S.Choi, A.Jhingran, P.Castillo, B.Lee, J.Wang, N.Hughes, M.Mohammadsaid, P.Balter |
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| | PO-GeP-M-317 : Optimal Image Registration for Combining Dose Distributions From External Beam and Brachytherapy for Combined Modality Prostate Radiation Therapy A.Cooney*, S.To, B.Lee, M.Lim, A.Riegel |
|
| | PO-GeP-M-318 : Optimal Planning Target Volume Margin for Lung SBRT with Minimal Immobilization C.Wilcken, T.Chow, M.Wierzbicki* |
|
| | PO-GeP-M-319 : Optimizing Treatment Plan Selection of HPV-Associated OPSCC Patients Using Artificial Intelligence On Electronic Medical Records and Radiomics T.Bejarano*, I.Mihaylov, M.Samuels |
|
| | PO-GeP-M-320 : Organ Segmentation From CT Images Using Super Perception Convolutional Neural Networks for Cervical Cancer Brachytherapy Z.Zhang*, S.Wang, Y.He, R.Zhou, Z.Jin, P.Xie, J.Wei |
|
| | PO-GeP-M-321 : Out of Sample Performance of a Deep Learning Based Registration Quality Assurance Method X.Zhou*, S.Galib, H.Lee, G.Hugo |
|
| | PO-GeP-M-322 : Out-Of-Field Radiation Dose Considerations in Partial Breast Irradiation with Elekta Unity MR-Linac - a Feasibility Study M.Muruganandham*, B.Lee, S.Vedam, J.Wang, J.Yang, M.Salehpour, S.Shaitelman |
|
| | PO-GeP-M-323 : Partial Volume Correction (PVC) in Quantitative 18F-FDG PET/CT Imaging On Intratumoral Dose Response Assessment S.Chen*, S.Chang, D.Krauss, D.Yan |
|
| | PO-GeP-M-324 : Patient Dose From Kilovoltage Radiographic Images During Synchrony Treatments On the Radixact System W.Ferris*, W.Culberson |
|
| | PO-GeP-M-325 : Patterns in the Diffusion Characteristics of Brain Metastases in Stereotactic Radiosurgery Patients Using Diffusion Weighted Imaging J.Madamesila*, N.Ploquin, E.Tchistiakova |
|
| | PO-GeP-M-326 : Performance Evaluation of the Twist-Correction System for Head and Neck Radiotherapy Driven by Remote Control H.Shimizu*, K.Sasaki, T.Aoyama, T.Kitagawa, T.Iwata, H.Fukuma, H.Tachibana, T.Kodaira |
|
| | PO-GeP-M-327 : Phantom with Randomly Distributed Anechoic Spheres for Assessing Lesion Detectability and Scan Setup of Ultrasound Transducers Z.Li*, C.Baiu, J.Chen, J.Zagzebski |
|
| | PO-GeP-M-328 : Pre-Clinical Evaluation of a Surface Imaging System for Intracranial Stereotactic Radiosurgery E.Covington*, C.Huyghe, S.Wiesner, D.Hanson, R.Popple |
|
| | PO-GeP-M-329 : Predicting Prognosis of Posterior Fossa Ependymoma Using MRI Radiomics L.Tam, D.Yecies, M.Han, K.Yeom, S.Mattonen* |
|
| | PO-GeP-M-330 : Predicting Successful Voluntary Breath-Hold Candidates by Monitoring Breathing During Simulation T.Nano, D.Capaldi, M.Feng, T.Solberg, A.Witztum* |
|
| | PO-GeP-M-331 : Predicting Treatment Outcome After Immunotherapy Based On Delta-Radiomic Model in Metastatic Melanoma X.Chen*, M.Zhou, K.Wang, Z.Wang, Z.Zhou |
|
| | PO-GeP-M-332 : Predicting Tumor Control Using Geometric Features of Hypoxia Measured with EPRI H.Smith*, I.Gertsenshteyn, B.Epel, E.Barth, M.Maggio, S.Sundramoorthy, H.Halpern |
|
| | PO-GeP-M-333 : Prediction of Optimal Weighting Factors Into the Objective Function On IMRT Plans E.Cisternas Jimenez*, F.Yin |
|
| | PO-GeP-M-334 : Prediction of Uterus Volume Shrinkage for Cervical Cancer Patients During Radiotherapy Using Machine-Learning Approach with Treatment Planning-CT Radiomic Features M.Nakano*, T.Nakamoto, Y.Kumai, Y.Koizumi, M.Sumi, K.Nawa, T.Imae, Y.Yoshioka, M.Oguchi |
|
| | PO-GeP-M-335 : Probabilistic Definition of the Clinical Target Volume -- Implications for Tumor Control Probability Modeling D.Craft*, T.Bortfeld |
|
| | PO-GeP-M-336 : Producing Clinical Data in Real-Time From An Automated and Paperless Workflow Implemented in Our Oncology Information System H.Miras Del Rio*, A.Bertolet Reina, A.Wals, J.Macias |
|
| | PO-GeP-M-337 : Prognostic Prediction for Lung Stereotactic Body Radiotherapy Using Breath-Hold CT-Based Radiomic Features with Random Survival Forest: A Multi-Institutional Study R.Kakino*, M.Nakamura, T.Mitsuyoshi, T.Shintani, M.Kokubo, Y.Negoro, M.Fushiki, M.Ogura, S.Itasaka, C.Yamauchi, S.Otsu, T.Sakamoto, M.Sakamoto, N.Araki, H.Hirashima, T.Adachi, Y.Matsuo, T.Mizowaki |
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| | PO-GeP-M-338 : Prognostic Value of Imaging-Based Estimates of Glioma Pathology Pre- and Post-Surgery E.Gates*, D.Suki, J.Weinberg, S.Prabhu, D.Fuentes, D.Schellingerhout |
|
| | PO-GeP-M-339 : Prospective Evaluation of Serial Quantitative MR Imaging of Patients with Brain Cancer On a 0.35T MR-Linac S.Nejad-Davarani*, N.Zakariaei, N.Hurst, S.Siddiqui, J.Snyder, T.Walbert, Y.Chen, E.Haacke, C.Glide-Hurst |
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| | PO-GeP-M-340 : Prostate Contour Variability in An MR-Only Prostate SBRT Workflow M.Davidson*, A.Shaaer, J.Stewart, D.Vesprini, J.Detsky, A.Loblaw, W.Chu, H.Chung, S.Liu, J.Shahi, M.Wronski, M.Ruschin, C.Mccann |
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| | PO-GeP-M-341 : Prostate Motion When Patient Coughs and Its Dosimetric Impact B.Guo, R.Tendulkar, P.Xia* |
|
| | PO-GeP-M-342 : Proton Radiography as a Means to Verify Surface-Imaging Localization Accuracy E.Gelover*, C.Chen, H.Li |
|
| | PO-GeP-M-343 : Prototyping a Morphological Positioning Robot for Radiotherapy R.Yang*, K.Bao, L.Zheng, P.Guan, F.Guo |
|
| | PO-GeP-M-344 : PTV Margin for Reduced Normal Tissue Dose VMAT Cranionspinal Irradiation M.Lin*, Z.Xiong, E.Chambers, N.Desai, A.Godley |
|
| | PO-GeP-M-345 : PTV Margin Reduction Study for 2-Phase Image-Guided VMAT Prostate Treatment S.Yaghoobpour Tari*, J.Dubicki, A.Hallock |
|
| | PO-GeP-M-346 : Quantification of Intra- and Interfractional Target Motion and Deformation in Gastric Cancer Radiotherapy M.Bleeker*, S.Lie, A.Bel, J.Sonke, M.Hulshof, A.van der Horst |
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| | PO-GeP-M-347 : Quantification of Intrafraction Prostate Motion Using Detected Features in Sagittal 2D Cine-MR B.Strbac*, C.Brouwer, S.Both, J.Langendijk, D.Yakar, S.Al-uwini |
|
| | PO-GeP-M-348 : Quantification of Prostate Positioning Accuracy and Movement During SBRT with CBCT Imaging K.Jones*, Z.Grelewicz, J.Van Schelt, A.Templeton, D.Wang, J.Turian |
|
| | PO-GeP-M-349 : Quantification of White Matter Hyperintensities Based On Diffusion Tensor Imaging and Support Vector Machine L.Zheng, R.Gao, W.Lu, L.Shi, W.Lu*, J.Qiu |
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| | PO-GeP-M-350 : Quantify the Difference in Target Margin Sharpness Demonstrated On 4DCT and 4DCBCT Images Y.Tseng*, M.Zhang, M.Hunt, Y.Song |
|
| | PO-GeP-M-351 : Quantifying Radiation-Induced Changes to Pulmonary Anatomy Through Dose-Binned Hounsfield Unit Analysis Pre- and Post-RT A.Wuschner*, E.Wallat, M.Flakus, D.Shanmuganayagam, J.Meudt, G.Christensen, J.Reinhardt, J.Bayouth |
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| | PO-GeP-M-352 : Quantifying the Effects of Radiation Therapy Fractionation Scheme On Dose Response Modeling E.Wallat*, A.Wuschner, M.Flakus, W.Shao, J.Reinhardt, G.Christensen, J.Bayouth |
|
| | PO-GeP-M-353 : Quantitative Analysis On KV-Based Motion Management During DIBH Lung SBRT T.Chen*, H.Wang, M.Malin, M.Tam, D.Barbee |
|
| | PO-GeP-M-354 : Quantitative Effect of MV Beam Scatter On Real-Time KV and Fluoroscopic Images W.Luo*, S.Zabinski, D.Pokhrel, Q.Chen, J.Allen, J.Molloy |
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| | PO-GeP-M-355 : Race-Telltales From Blinded Notes? Clinical Evidence Or Implicit Bias H.Zhou, D.Ruan* |
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| | PO-GeP-M-356 : Radiation Hardness of Cadmium Telluride Solar Cells in Proton Therapy Beam Mode S.Cho*, S.Ahn, J.Song |
|
| | PO-GeP-M-357 : Radiobiological and Physical Evaluation of the Effect of Metal Artifacts with VMAT and IMPT Plans T.Lee*, W.Hsi, Y.Mekuria |
|
| | PO-GeP-M-358 : Radiomics Feature Robustness Under Different Image Perturbation Combinations and Intensities: A Study On Nasopharyngeal Carcinoma CT Images J.Zhang, X.Teng*, Z.Ma, T.Yu, S.Lam, F.Lee, K.Au, W.Yip, J.Cai |
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| | PO-GeP-M-359 : Raw-Data Effective Atomic Number and Electron Density Assessment Accuracy: A Phantom Study C.Schaeffer*, S.Leon, C.Olguin, M.Arreola |
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| | PO-GeP-M-360 : Real-Time Long Range Respiratory Prediction J.Prinable*, R.O'Brien |
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| | PO-GeP-M-361 : Real-Time Target Tracking in Fluoroscopy Imaging Using Unet with Convolutional LSTM T.Peng*, Z.Jiang, Y.Chang, L.Ren |
|
| | PO-GeP-M-362 : Real-Time Verification and Quantification of Breath-Hold Reproducibility During Treatment for Liver and Lung SBRT A.Antolak*, N.Woody, K.Stephans, P.Xia, B.Guo |
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| | PO-GeP-M-363 : Real-Time Volumetric Image Guidance From a Single Projection View Via Deep Learning: A Preliminary Study X.Liang*, W.Zhao, L.Xing |
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| | PO-GeP-M-364 : Reconstruction of Intrafractional 3D Images From Real-Time 2D KV Radiograph and 4DCT J.Kim*, G.Chen, A.Tai, S.Lim, T.Keiper, X.Li, H.Zhong |
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| | PO-GeP-M-365 : Reducing Effective Dose and Cancer Risk for An Interplanetary Space Mission with Magnetic Shielding K.Ferrone*, C.Willis, J.Ma, L.Peterson, F.Guan, S.Kry |
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| | PO-GeP-M-366 : Reducing IMRT QA Workload by 95% and Keeping the Same Level of Quality Control T.Nano*, M.Descovich, E.Hirata, Y.Interian, G.Valdes |
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| | PO-GeP-M-367 : Region Specific Dose Prediction Using Deep Neural Networks: A Feasibility Study On the Planning Target Volume of Prostate IMRT Patients D.Nguyen*, S.Jiang |
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| | PO-GeP-M-368 : Residual Learning by An Artificial Neural Network for a Radiotherapy Beam Monitoring System Y.Cho*, M.Farrokhkish, B.Norrilnger, R.Heaton, J.David, M.Islam |
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| | PO-GeP-M-369 : Results of a Prospective Trial Examining MRI Sialography Guided Parotid Ductal Sparing D.Fried*, T.Zhu, S.Das, L.Marks, C.Shen, K.Pearlstein, B.Chera |
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| | PO-GeP-M-370 : Robustness Study of Deep Learning Based Medical Image Segmentation to Noisy Annotation S.Yu*, E.Zhang, J.Wu, H.Yu, L.Ma, Z.Yang, M.Chen, X.Gu, W.Lu |
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| | PO-GeP-M-371 : ROdiomX: A New Validated Software for the Radiomics Analysis of Medical Images in Radiation Oncology H.Bagher-Ebadian*, M.Lu, F.Siddiqui, A.Ghanem, N.Wen, Q.Wu, B.Movsas, I.Chetty |
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| | PO-GeP-M-372 : RT PACS Is Becoming An Indispensable Information System for Clinical Practice and Research in Radiation Oncology Y.Yan*, W.Lu, J.Wu, M.Lin, X.Gu, S.Jiang |
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| | PO-GeP-M-373 : Scoring Contour Agreement Using a Beta Distribution Model T.Lim*, X.Wang, J.Yang |
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| | PO-GeP-M-374 : Segmentation Accuracy and Radiomics Feature Stability of Multiple U-Net Based Automatic Segmentations On Ultrasound Images for Patients with Ovarian Cancer X.Jin*, J.Jin, C.Xie |
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| | PO-GeP-M-375 : Self-Supervised Deep Learning for Low-Dose CT Image Denoising T.Bai*, D.Nguyen, S.Jiang |
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| | PO-GeP-M-376 : Semi-Automatic Contouring for Prostate Cancer Patients Based On Random Forest Classifier and Active Contour Algorithm D.Tewatia*, R.Tolakanahalli |
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| | PO-GeP-M-377 : Sensing Changes in Tumor During Boron Neutron Capture Therapy Using PET with a Collimator: Simulation Study H.Yang*, D.Yoon, T.Suh |
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| | PO-GeP-M-378 : Setup and Intrafractional Motion Error in the Hypo-Fractionated Brain Radiosurgery and the Effectiveness of Bite Block E.Han*, S.Krafft, T.Briere |
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| | PO-GeP-M-379 : Should Anchored Lung Beacons Motion Correlation with Lung Tumor Motion Be Evaluated Using 4DCT for Every Patient? D.Soultan, H.Saleh, |
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| | PO-GeP-M-380 : Simplifying 3D Bolus Creation Using 3D Slicer P.Koistinen*, M.Koistinen |
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| | PO-GeP-M-381 : Single Imager Proton Radiography with a Pencil-Beam Scanning System J.Harms, L.Maloney, Y.Lin, T.Liu, A.Erickson, R.Zhang* |
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| | PO-GeP-M-382 : Six Dimensional Cranial Motion Detection Using a Novel Capacitive Monitoring Technology P.Sadeghi*, J.Robar |
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| | PO-GeP-M-383 : Skin Dose Comparison Between a 1.5 T MR-Linac and a Conventional Linac Using Optically Stimulated Luminescence Dosimeters for Patients with Intracranial Tumors A.Kim*, C.Mccann, M.Ruschin, C.Tseng, A.Sahgal, B.Keller |
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| | PO-GeP-M-384 : Statistical Process Control Analysis of Adaptive Patient Specific QA On the Elekta Unity MRI-Linac S.Strand*, A.Boczkowski, J.Snyder, D.Hyer, S.Yaddanapudi, D.Dunkerley, J.St-Aubin |
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| | PO-GeP-M-385 : Stereotactic Space Definition Accuracy in the Latest Gamma Knife Icon Based Radiosurgery B.Liu*, T.Cui, D.Shabbar, J.Weiner, N.Yue, K.Nie |
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| | PO-GeP-M-386 : Study of Segmental Spinal Cord Contour Expansion Margin for Esophageal Cancer Patient Under Radiation Treatment L.Dingjie*, S.Wei, C.Yang, H.Ge |
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| | PO-GeP-M-387 : Study of the In-Air Electron Streaming Effect for Lung SBRT with a 1.5T MR-Linac H.Liu*, S.Ding, B.Wang, Y.Li, Y.XIA, Y.Sun, X.HUANG |
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| | PO-GeP-M-388 : Study On Intelligent Treatment Planning for Left Breast Cancer H.Xiaodong*, B.Su, R.Zhao |
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| | PO-GeP-M-389 : Surveillance of Conventionally Fractionated Lung Radiotherapy Using a CBCT Dose Calculation Framework - a Preliminary Study G.Lasio*, B.Zhang, S.Lee, A.Gopal, B.Yi |
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| | PO-GeP-M-390 : Synthetic Contrast Enhancement of Cone Beam Computed Tomography (CBCT) for Adaptive Radiotherapy O.Dona*, Y.Wang, D.Horowitz, A.Xu, J.Rickman, C.Wuu |
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| | PO-GeP-M-391 : Synthetic Fluoroscopic Image Generation for Tracking Accuracy Validation of Marker-Less Tumor Tracking in Radiotherapy K.Miyazaki*, T.Fujii, T.Umekawa, N.Miyamoto, K.Umegaki |
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| | PO-GeP-M-392 : Target Tracking in Kilovoltage Images Using Templates of Fiducial Constellations G.Angelis*, B.Zwan, A.Briggs, D.Nguyen, P.Keall, J.Booth |
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| | PO-GeP-M-393 : Techniques and Strategies for Minimizing Reconstruction Artifacts in Extended FOV CT Used for Radiation Therapy Treatment Planning S.Scarboro*, A.Polemi, E.Aliotta, P.Collins |
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| | PO-GeP-M-394 : The Commissioning of DLG Correction Factor for Mobius3D b.wang*, B.Yang, J.Qiu |
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| | PO-GeP-M-395 : The Content-Based Standardizing Nomenclatures (CBSN) in Radiotherapy for Nasopharyngeal Carcinoma OARs X.MAI, S.HUANG, Z.Zhong, w.zheng, S.Chen, S.Zhou, s.Huang, Y.XIA, X.HUANG, X.Yang* |
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| | PO-GeP-M-396 : The Correction Term of a Three-Pool Kinetic Model for In Vitro Anaerobic Glycolysis Under MRI C.Hsieh*, K.Lu, G.Lin, C.Wu, F.Chen |
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| | PO-GeP-M-397 : The Effect of Couch and Gantry Angles On Patient Monitoring Using An Optical Surface Monitoring System Equipped with the Advanced Camera Calibration Feature P.Mone, D.Workie* |
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| | PO-GeP-M-398 : The Feasibility of Using Radiomics to Detect T-Spine Lytic Bone Metastases in Simulation-CT Images H.Naseri*, J.Kildea |
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| | PO-GeP-M-399 : The Impact of 5D Accumulated Dose On Toxicity Predictions Compared to Planned Dose for Non-Small Cell Lung Cancer Treated with IMRT and PSPT Y.He*, U.Titt, Z.Liao, J.Pollard-Larkin, P.Balter, R.Mohan, K.Brock |
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| | PO-GeP-M-400 : The Impact of CT Reconstruction Kernels On Atlas Based Automatic Segmentation M.Reyhan*, B.Swann, I.Vergalasova, N.Yue, K.Nie, R.Singh, M.McKenna |
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| | PO-GeP-M-401 : The Optimization of Spectra Gap for Proton Stopping Power Estimation Using Dual-Energy CT Image Domain Method D.Han*, S.Zhang, K.Ding |
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| | PO-GeP-M-402 : The Use of Image Reject Analysis to Improve Imaging Within a Radiation Therapy Department L.Buckley* |
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| | PO-GeP-M-403 : To Distinguish Peripheral Lung Cancer and Pulmonary Inflammatory Pseudotumor Using CT-Radiomics Features Extracted From PET/CT Images C.Ma, Y.Yin* |
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| | PO-GeP-M-404 : To Tweak Or Not to Tweak? Prospects for Daily Online Adaptation Using Unedited CBCT Auto-Segmentation M.Moazzezi, K.Moore, K.Kisling, C.Bojechko, X.Ray* |
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| | PO-GeP-M-405 : TOPAS Model for Simulating Contrast in High-Energy Proton Radiography B.Broder*, M.Freeman |
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| | PO-GeP-M-406 : Toward Real-Time MR-Guided Adaptive Radiotherapy Planning Using a Deep Convolutional Conditional Generative Adversarial Network L.Buchanan*, Y.Zhang, X.Chen, F.Ceballos, Y.Liang, X.Li |
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| | PO-GeP-M-407 : Towards a Mathematical Framework to Address Uncertainty, Adaptation Cost and Tractability in Robust Adaptive Radiation Therapy M.Boeck* |
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| | PO-GeP-M-408 : Towards Safer Artificial Intelligence-Based Radiation Therapy Treatment Planning: Adding Uncertainty Estimation to Volumetric Dose Prediction Using An Approximate Bayesian Method On Deep Neural Networks D.Nguyen*, A.Balagopal, A.Sadeghnejad Barkousaraie, R.McBeth, S.Jiang |
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| | PO-GeP-M-409 : Transferring Beam Navigation Behavior From Human to Robot: An Evidence Driven Decision Making Model for Liver SBRT Y.Sheng*, W.Wang, R.Li, C.Wang, J.Zhang, X.Li, H.Stephens, Q.Wu, F.Yin, Y.Ge, Q.Wu |
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| | PO-GeP-M-410 : Treatment of Oligoresistant and Oligoprogressive Disease in Metastatic Prostate Cancer Patients with Radiation Therapy A.Roth*, G.Cooley, J.Smilowitz, P.Ferjancic, G.Liu, R.Jeraj |
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| | PO-GeP-M-411 : Treatment Planning for Patients with Resected GBM: Is Post-Operative MRI Enough? S.Thrower*, K.Brock, Y.Hasan, C.Chung |
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| | PO-GeP-M-412 : Unboxing Artificial Intelligence "black-Box" Models - A Novel Heuristic S.Weppler*, H.Quon, N.Harjai, C.Beers, L.Van Dyke, C.Kirkby, C.Schinkel, W.Smith |
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| | PO-GeP-M-413 : Understanding Radiomics Interconnections Using Network Graphs A.Apte*, A.Iyer, J.Deasy, J.Oh |
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| | PO-GeP-M-414 : Using Daily Image-Guidance CBCT Scans to Determine the Impact On Delivered Dose From Variations in Bladder and Rectal Filling During IMRT for High-Risk Prostate Cancer W.Martin*, D.Mynampati, W.Bodner, K.Garcia, S.Hsu, J.Yap, M.Garg, S.Kalnicki, W.Tomé, P.Brodin |
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| | PO-GeP-M-415 : Using Radiomics to Study Statin Use and Omega-3 Use in Prostate Cancer Patients D.Zheng*, Y.Shi, E.Wahle, L.Krajewski, X.Liang, Q.Du, C.Zhang, S.Zhou, M.Baine |
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| | PO-GeP-M-416 : Using Raman Spectroscopy and Machine Learning to Predict and Monitor Cellular Radiation Responses X.Deng*, K.Milligan, R.Ali-Adeeb, P.Shreeves, S.Van Nest, J.Andrews, A.Brolo, J.Lum, A.Jirasek |
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| | PO-GeP-M-417 : Using Very Small Contour Sets to Train High-Quality Deep-Learning Segmentation Models Y.Zhao*, D.Rhee, C.Cardenas, L.Court, J.Yang |
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| | PO-GeP-M-418 : Utilizing Knowledge-Based Planning Model to Predict Achievable Prescription Dose for Mesothelioma Patients with Two Intact Lungs L.KUO*, A.Rimner, E.Yorke |
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| | PO-GeP-M-419 : Validation and Clinical Application of DL-Based Automatic Target and OAR Segmentation Software, DeepViewer Z.Peng*, Y.Chang, Y.Song, H.Wu, A.Wu, X.Pei, X.Xu |
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| | PO-GeP-M-420 : Validation of a Commercial Continuous Hounsfield Unit (HU) Pelvis Synthetic CT Platform for MR-Only Prostate Radiotherapy Treatment Planning V.Yu*, M.Hunt, L.Cervino, A.Damato, N.Tyagi |
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| | PO-GeP-M-421 : Validation of a Near-Infrared Pupil-Tracking Tool for Robotic Radiosurgery of Ocular Tumors J.Mégrourèche*, K.Zerouali, F.DeBlois, D.Roberge, S.Bedwani |
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| | PO-GeP-M-422 : Validation of An AI-Driven Treatment Planning System for Adaptive Radiotherapy E.Pryser*, B.Cai, F.Reynoso, E.Laugeman, L.Henke, H.Kim, S.Mutic, G.Hugo |
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| | PO-GeP-M-423 : Validation of An Automatic ACR Phantom Quality Assurance Tool for the Low-Field MR Guided Radiotherapy System Y.Gao*, R.Lotey, P.Hu, Y.Yang |
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| | PO-GeP-M-424 : Validation of An Optical Surface Monitoring System to Detect Submillimeter Surface Displacements at Non-Zero Couch Angles D.Pinkham*, S.Kamath, A.Yu, S.Hancock |
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| | PO-GeP-M-425 : Validation of Four-Dimensional Computed Tomography Without An External Respiratory Signals Device for the Radiotherapy Planning of Lung Cancer Patients Y.Shimohigashi*, Y.Doi, Y.Kono, M.Maruyama, Y.Kai, R.Toya |
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| | PO-GeP-M-426 : Validation of Intrafraction Motion Review Using Dual Surrogate in Prospective Clinical Study A.Cetnar*, A.Ayan, G.Graeper, M.Weldon, K.Woods, N.Gupta |
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| | PO-GeP-M-427 : Value Proposition of Online Adaptive Radiotherapy: Clinically Achieved Improvements in Daily Delivered Dose J.Bayouth*, L.Bayouth, P.Yadav, A.Shepard, A.Baschnagel, M.Bassetti, K.Mittauer |
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| | PO-GeP-M-428 : Versatile Geometric Distortion Evaluation of MRI Using Modular Phantom with LEGO Compatibility in Radiation Therapy C.Hong*, H.Cho, C.Lee, B.Ahn |
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| | PO-GeP-M-429 : Virtual Acquisition: Efficient, Accurate and Low-Dose KV-Projection Based Positioning H.Yan*, J.Li, Z.Wang, C.Deng, X.Li, C.Ma, J.Li |
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| | PO-GeP-M-430 : VMAT Case Study for Patient Specific Virtual Compensator Algorithm EPID In-Vivo Dosimetry J.Barbiere*, R.Teboh Forbang, A.Ndlovu |
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| | PO-GeP-M-431 : Voxel Forecast Classifier to Predict Spatially Variant Binary Tumor Voxel Response On Longitudinal FDG-PET/CT Imaging of FLARE-RT Protocol Patients S.Bowen*, D.Hippe, W.Chaovalitwongse, P.Thammasorn, X.Liu, R.Iranzad, R.Miyaoka, H.Vesselle, P.Kinahan, R.Rengan, J.Zeng |
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| | PO-GeP-M-432 : Weakly-Supervised Deep Learning Based Automatic Image Segmentation Via Deformable Image Registration W.Chi*, W.Lu, L.Ma, J.Wu, H.Chen, M.Tan, X.Gu |
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| | PO-GeP-M-433 : Weekly Vs. Daily Online Adaptation for Head and Neck Intensity-Modulated Proton Therapy M.Bobic*, A.Lalonde, G.Sharp, C.Grassberger, J.Verburg, B.Winey, A.Lomax, H.Paganetti |
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| | PO-GeP-M-434 : What Is the Dosimetric Benefit of Weekly and Daily Adaptive Replanning for Prostate Cancer Patients? M.Splinter*, T.Bostel, P.haering, C.Lang, N.Nicolay |
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| | PO-GeP-M-435 : White Matter Fiber Tract Abnormalities by Voxel Wise Correlation Analysis in Neurodegenerative Disease R.Juh*, J.Han, C.Kim, C.Oh, T.Suh |
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| | PO-GeP-M-436 : Why MAE Alone Is Not Enough for SCT Model Comparisons P.Klages*, N.Tyagi, H.Veeraraghavan |
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| | PO-GeP-M-437 : Young-S Modulus Reconstruction From Ultrasound Breast Images C.Rabin*, N.Benech |
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| | PO-GeP-M-438 : The Effect of Dose Calculation Accuracy for HU to Electron Density Calibration For Iterative CBCT Reconstruction J.Zavala Bojorquez*, E.Flores-Martinez, T.Atwood, C.Bojechko |
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| | PO-GeP-M-439 : Comparison of a 3D Convolutional Neural Network Segmentation Method to Traditional Atlas Segmentation for CT Head and Neck Contours A.Kruzer*, H.Wan, M.Bending, C.Halley, D.Darkow, D.Pittock, N.Cole, P.Jacobs, A.Nelson |