| Re-Imagining CT Methodology |
SU-KL-DBRB-5: Emerging and Preclinical Modalities
A Computational Forward Model for Propagation-Based Phase Contrast CT in a Cone Beam Geometry |
Elisabeth Shanblatt |
|
| Emerging Modalities and Platforms |
SU-KL-DBRB-1: Emerging and Preclinical Modalities
BEST IN PHYSICS (IMAGING): Optimization of a Table-Top X-Ray Fluorescence Computed Tomography (XFCT) System |
Chelsea Dunning |
|
SU-KL-DBRB-8: Emerging and Preclinical Modalities
Analysis of Pharmacokinetic Modeling and Doxycycline to Quantify Tumor Metabolism Variations Using Hyperpolarized [1-13C]-Pyruvate Magnetic Resonance Imaging |
Joshua Niedzielski |
|
SU-KL-DBRB-9: Emerging and Preclinical Modalities
Hyperpolarized Magnetic Resonance Imaging Reveals Transformations in Pyruvate Metabolism Prior to Anatomic Changes in Patient-Derived Glioblastoma Models |
Travis Salzillo |
|
SU-KL-DBRB-11: Emerging and Preclinical Modalities
Characterizing Thrombus Age and Molecular Organization Using Magnetic Nanoparticle Spectroscopy |
John Weaver |
|
| Response Assessment |
SU-L-KDBRC-6: Imaging for Treatment Response Assessment
Apparent Diffusion Coefficient (ADC) Measured by Diffusion Weighted MRI Was Highly Correlated with Tumor Cell Survival in Non-Small Cell Lung Cancer (NSCLC) Cell Lines Under Stereotactic Body Radiotherapy (SBRT) Regimens |
Yuenan Wang |
|
| Re-Imagining CT Methodology |
MO-AB-KDBRA1-2: John R. Cameron Young Investigator Symposium
A Stationary Computed Tomography Module Using Photocathode-Driven X-Ray Sources |
Avilash Cramer |
|
| Emerging Modalities and Platforms |
MO-AB-KDBRA1-9: John R. Cameron Young Investigator Symposium
Optimization of a Spectroscopic Photoacoustic Imaging Technique to Noninvasively Assess Oxygen Saturation in Murine Femoral Bone Marrow |
Cayla Wood |
|
MO-AB-KDBRA1-10: John R. Cameron Young Investigator Symposium
A Novel Multi-Projection Bioluminescence Tomography for Small Animal Radiation Research Platform (SARRP) |
Xiangkun Xu |
|
MO-K-KDBRC-7: Advanced Computing Applications
A Virtual Reality Platform for Medical Imaging Analysis and Radiation Therapy Planning |
Christopher Williams |
|
| Functional Imaging |
MO-AB-KDBRA1-4: John R. Cameron Young Investigator Symposium
Diffusion-Prepared Multi-Shot BSSFP Imaging with Gradient Stabilizer for High-Resolution and Distortion-Free Diffusion Imaging |
Yu Gao |
|
MO-K-DBRB-2: Quantitative Imaging: PET/CT, PET/MR, and MR
Improved PET Quantification by Adaptive Denoising and Regularized Image Reconstruction: A Feasibility Study |
Mauro Namias |
|
| Informing Therapy with Biology |
MO-AB-KDBRA1-6: John R. Cameron Young Investigator Symposium
Mapping Biological Effects Along a Scanned 81.4 MeV Proton Beam: LET Modulation of the DNA Repair Response |
Lawrence Bronk |
|
MO-K-DBRA-5: Data Science: Applications in Radiation Therapy
Incorporating a Novel Radiomics Framework for Biologically Optimised Prostate RadioTherapy (BiRT) |
Annette Haworth |
|
MO-K-KDBRC-6: Advanced Computing Applications
JACK KROHMER JUNIOR INVESTIGATOR COMPETITION WINNER: Selecting Predictive Genomic Biomarkers for Oropharyngeal Cancer Treatment Prediction by Use of Advanced Machine Learning Method |
Jian Wu |
|
| Ensuring Safety, Quality, and Efficiency |
MO-K-KDBRC-1: Advanced Computing Applications
Automated Standardization of Organ Labeling in Head and Neck Using Deep Learning |
Timothy Rozario |
|
MO-K-DBRA-2: Data Science: Applications in Radiation Therapy
BEST IN PHYSICS (THERAPY): Health Information Gateway and Exchange (HINGE): Radiation Oncology Data Analytics Portal |
Joseph Nalluri |
|
| New Approaches to Quantify Dose |
MO-AB-KDBRA1-1: John R. Cameron Young Investigator Symposium
A Novel SPECT/CT-Based Lung Dose Estimation for Treatment Planning in Y90 Microsphere Radioembolization Therapy |
Benjamin Lopez |
|
MO-AB-KDBRA1-8: John R. Cameron Young Investigator Symposium
Scintillator Target Imaging Provides Accurate Remote Multi-Site Surface Dosimetry |
Irwin Tendler |
|
MO-K-DBRA-8: Data Science: Applications in Radiation Therapy
Volumetric Dose Prediction On Head and Neck Cancer Patients with a Novel Deep Learning Architecture: Hierarchically Densely Connected U-Net |
Dan Nguyen |
|
| MRI in RT |
MO-K-KDBRC-2: Advanced Computing Applications
BEST IN PHYSICS (JOINT IMAGING-THERAPY): Deep Learning Mapping of CT to MRI for Longitudinal Tracking of Lung Tumors for MRI-Guided Radiotherapy |
Jue Jiang |
|
| Response Assessment |
MO-K-DBRB-5: Quantitative Imaging: PET/CT, PET/MR, and MR
Automated Evaluation of Proton Therapy Related Changes in Intracranial Vessel Diameter On Longitudinal Magnetic Resonance Angiography |
Chihyang Hsu |
|
| Prediction and Classification |
MO-K-KDBRC-6: Advanced Computing Applications
JACK KROHMER JUNIOR INVESTIGATOR COMPETITION WINNER: Selecting Predictive Genomic Biomarkers for Oropharyngeal Cancer Treatment Prediction by Use of Advanced Machine Learning Method |
Jian Wu |
|
| Artificial Intelligence and Machine Learning |
MO-K-DBRA-4: Data Science: Applications in Radiation Therapy
Feasibility of Using Machine Learning Techniques to Predict the Results of VMAT Patient-Specific QC Measurements |
Dal Granville |
|
MO-K-DBRA-8: Data Science: Applications in Radiation Therapy
Volumetric Dose Prediction On Head and Neck Cancer Patients with a Novel Deep Learning Architecture: Hierarchically Densely Connected U-Net |
Dan Nguyen |
|
MO-K-KDBRC-1: Advanced Computing Applications
Automated Standardization of Organ Labeling in Head and Neck Using Deep Learning |
Timothy Rozario |
|
MO-K-KDBRC-2: Advanced Computing Applications
BEST IN PHYSICS (JOINT IMAGING-THERAPY): Deep Learning Mapping of CT to MRI for Longitudinal Tracking of Lung Tumors for MRI-Guided Radiotherapy |
Jue Jiang |
|
MO-K-KDBRC-3: Advanced Computing Applications
Automated Detection of Vertebral Body Metastases for Fully-Automated Palliative Radiotherapy Using Transfer Learning |
Tucker Netherton |
|
MO-K-KDBRC-4: Advanced Computing Applications
An Automated Method to Generate Patient-Specific Dose Distributions for Radiotherapy Using Deep Learning |
Xinyuan Chen |
|
MO-K-KDBRC-6: Advanced Computing Applications
JACK KROHMER JUNIOR INVESTIGATOR COMPETITION WINNER: Selecting Predictive Genomic Biomarkers for Oropharyngeal Cancer Treatment Prediction by Use of Advanced Machine Learning Method |
Jian Wu |
|
| Novel Detection Technologies |
TU-D-KDBRB1-2: Imaging for Particle Therapy
First Demonstration of a Prompt Gamma Slit-Camera for in Vivo Proton Range Verification Based On Semiconductor Detectors |
Hui Wang |
|
TU-D-KDBRB1-3: Imaging for Particle Therapy
Comparison of Acoustic Detection Methods for Proton Range Verification |
Wei Nie |
|
TU-D-KDBRB1-6: Imaging for Particle Therapy
Proton Range Verification with Submillimeter Precision Using a Full-Scale Prototype Prompt Gamma-Ray Spectroscopy System |
Joost Verburg |
|
| Artifact and Noise Mitigation |
TU-AB-202-2: Breast Imaging
BEST IN PHYSICS (IMAGING): Evaluation of An Automated Grid Artifact Detection System for Quality Control in Digital Mammography |
Christopher MacLellan |
|
TU-AB-202-4: Breast Imaging
Back-Projection Filtration Image Reconstruction Approach for Reducing High-Density Object Artifacts in Digital Breast Tomosynthesis |
Hyeongseok Kim |
|
TU-AB-202-9: Breast Imaging
Reconstruction Algorithm Design for Mitigating the Orientation Dependent Conspicuity of Fiber-Like Signals in Digital Breast Tomosynthesis |
Sean Rose |
|
TU-K-DBRB-3: Quantitative Imaging: CT and MRI
Application and Performance Evaluation of a Modified BM3D Denoising Method to Emphysema Scoring On Ultra-Low-Dose CT Images |
Tingting Zhao |
|
| Emerging Modalities and Platforms |
TU-GH-KDBRC-8: Advances in Imaging Technology
An Endoscopic 3-D OCT Imaging System for Detection of Early Stage Pancreatic Cancer |
Lanchun Lu |
|
TU-K-207-6: Multimodality, Optical Imaging, and Ultrasound
Photoacoustic CT to Characterize Acute and Chronic Hypoxia |
Devin Miles |
|
| Functional Imaging |
TU-D-202-3: Nuclear Medicine
GPET: An Efficient and Accurate Simulation Tool Via GPU-Based Monte Carlo for PET |
Yujie Chi |
|
TU-GH-KDBRA1-8: Radiobiology: Experiments and Modeling
Theranostics of Murine Breast Cancer with a 86/90Y-Labeled Antibody |
Emily Ehlerding |
|
TU-GH-KDBRA1-9: Radiobiology: Experiments and Modeling
Antibody and Fragment-Based PET Imaging of CTLA-4+ T-Cells in Humanized Mouse Models |
Emily Ehlerding |
|
TU-K-207-7: Multimodality, Optical Imaging, and Ultrasound
Removing Noise Bias in Photoacoustic-Based SO2 Estimates: A Simple Empirical SNR-Adaptive Thresholding Approach |
Diego Sampaio |
|
| Informing Therapy with Biology |
TU-GH-KDBRA1-1: Radiobiology: Experiments and Modeling
Double Strand Break (DSB) Complexity and Proximity Effects Within the Repair-Misrepair Fixation (RMF) Model for Improved Predictions of Cell Survival From Heavy Ions |
Michael Butkus |
|
TU-GH-KDBRA1-2: Radiobiology: Experiments and Modeling
Interstitial Diffuse Optical Probe with Optical Fiber Spectroscopy to Measure Dynamic Tumor Hypoxia |
Leonard Che Fru |
|
TU-GH-KDBRA1-5: Radiobiology: Experiments and Modeling
Oxygen Microbubbles Transiently Relieve Tumor Hypoxia and May Improve Radiation Therapy Tumor Control |
Sha Chang |
|
TU-GH-KDBRA1-10: Radiobiology: Experiments and Modeling
Role of Double Strand Break DNA Repair Deficiency On the Sensitivity of Cells to Therapeutic Proton Beams |
Scott Bright |
|
| Precision in Treatment Delivery |
TU-GH-KDBRA1-11: Radiobiology: Experiments and Modeling
BEST IN PHYSICS (THERAPY): Enhanced Drug Delivery by Nanoparticle and Radiation-Mediated Tumor Vascular Modulation |
Sijumon Kunjachan |
|
TU-K-KDBRC-7: Dose Calculation, Delivery and Measurement Techniques
Using Dual Step Wedge and 2D Scintillator to Achieve Highly Precise and Robust Proton Range Quality Assurance |
Wei Deng |
|
| New Approaches to Quantify Dose |
TU-K-KDBRC-2: Dose Calculation, Delivery and Measurement Techniques
An Energy-Adaptive Finite Element Angular Discretization Towards a Fast Deterministic Dose Calculation in Magnetic Fields |
Joel St-Aubin |
|
TU-K-KDBRC-4: Dose Calculation, Delivery and Measurement Techniques
BEST IN PHYSICS (THERAPY): Entropic Model for Real-Time Dose Calculation |
Gabriele Birindelli |
|
TU-K-KDBRC-8: Dose Calculation, Delivery and Measurement Techniques
Aerrow: A Probe-Format Graphite Calorimeter for Absolute Dosimetry of MR-Guided Radiotherapy Modalities |
James Renaud |
|
| Real-Time Treatment Guidance |
TU-AB-205-3: X-Ray Based Imaging for Therapy Guidance
Probabilistic Decomposition of X-Ray Image Sequence to Extract Obscure Target Objects for Monitoring Intrafractional Organ Motion |
Masahiro Shindo |
|
TU-D-KDBRB1-1: Imaging for Particle Therapy
Instantaneous Full Field Proton Radiography for Image Guidance |
Matthew Freeman |
|
| Response Assessment |
TU-GH-KDBRC-10: Advances in Imaging Technology
Advances in Imaging of Radiation Therapy Response in Soft Tissue Sarcomas Using Magnetic Resonance Elastography (MRE) and Dynamic Contrast-Enhanced (DCE)-MRI |
Kay Pepin |
|
TU-D-DBRB-3: Quantitative Imaging: Ultrasound, CT, and PET/CT Applications
Combined Morphologic and Metabolic Pipeline for Treatment Response Evaluation - a Pilot Study On Pancreatic Adenocarcinoma Patients |
Yi Lao |
|
| Prediction and Classification |
TU-K-207-1: Multimodality, Optical Imaging, and Ultrasound
Early Prediction of Locoregional Recurrence in Head & Neck Cancer After Radiation Therapy Through Multifaceted Radiomics |
Zhiguo Zhou |
|
TU-AB-DBRB-6: Quantitative Imaging: Translation to Practice
Could Radiomic Signature Developed From NSCLC Patients Predict Overall Survival of Patients with ALK+ Mutation? |
Lyu Huang |
|
TU-AB-DBRB-7: Quantitative Imaging: Translation to Practice
CT-Based Radiomic Analysis for Prediction of Liver Progression Risk in Hepatocellular Carcinoma Patients Treated with Stereotactic Body Radiation Therapy |
Lise Wei |
|
TU-K-202-2: Computed Tomography I
A Radiomics Nomogram Model to Preoperatively Predict Histologic Grade in Pancreatic Neuroendocrine Tumors |
Pengfei Yang |
|
| Artificial Intelligence and Machine Learning |
TU-AB-DBRB-5: Quantitative Imaging: Translation to Practice
Automatic Segmentation of the Prostate Gland On Planning CT Images Using Deep Neural Networks (DNN) |
Chang Liu |
|
TU-D-DBRB-5: Quantitative Imaging: Ultrasound, CT, and PET/CT Applications
Automatic Liver and Tumor Segmentation Using Hierarchical Convolutional-Deconvolutional Neural Networks with Jaccard Distance |
Yading Yuan |
|
TU-K-202-4: Computed Tomography I
Automated Segmentation of Malignant Pleural Mesothelioma Tumor On Computed Tomography Scans Using Deep Convolutional Neural Networks |
Eyjolfur Gudmundsson |
|
| Artifact and Noise Mitigation |
WE-AB-KDBRB1-6: Novel Imaging Modalities and Applications
BEST IN PHYSICS (JOINT IMAGING-THERAPY): ACROBEAT: Adaptive CaRdiac COne BEAm Computed Tomography |
Tess Reynolds |
|
WE-FG-207-4: Computed Tomography II
Automated-Adaptive Iterative Metal Artifact Reduction: Quantitative Evaluation of Streak Artifact Reduction When Reconstructing CT Images in Presence of Metal |
Nilesh Mistry |
|
| Emerging Modalities and Platforms |
WE-AB-KDBRB1-10: Novel Imaging Modalities and Applications
An Investigation of the Optical Properties Dependence for Cherenkov Imaging of TSET |
Timothy Zhu |
|
| Functional Imaging |
WE-AB-202-9: Magnetic Resonance Imaging
Quality Assessment and Repeatability Measurement On DCE-MRI-Derived Blood Volume in Individual Patients During a Clinical Trial |
Madhava Aryal |
|
WE-AB-KDBRC-4: Longitudinal and Functional Imaging
Clinical Validation of Four-Dimensional Computed Tomography-Based Lung Ventilation Images Using Texture Feature Analysis and Pulmonary Function Test |
Hao Zhang |
|
WE-AB-KDBRB1-11: Novel Imaging Modalities and Applications
Distinguishing Immunotherapy Resistant and Sensitive Melanoma Xenografts Using 13C-MRS of Hyperpolarized Pyruvate and 1H-NMR Metabolomics |
Prasanta Dutta |
|
WE-FG-207-5: Computed Tomography II
Dialysate Cooling During Hemodialysis: Assessment of Liver Hemodynamics Using CT Perfusion Imaging |
Raanan Marants |
|
| Intelligent Treatment Planning |
WE-FG-DBRA-1: Knowledge-based Treatment Planning
Automated IMRT Treatment Planning Using Expedited Constrained Hierarchical Optimization (ECHO): Retrospective Study and Clinical Implementation |
Masoud Zarepisheh |
|
WE-FG-DBRA-2: Knowledge-based Treatment Planning
BEST IN PHYSICS (THERAPY): Manual Plan Refinement Offers Little to No Improvement Over Knowledge-Based Automated Plans Across Multiple Disease Sites |
Robert Kaderka |
|
WE-FG-DBRA-3: Knowledge-based Treatment Planning
Ensemble Learning: A Case Study with Knowledge Based Treatment Planning |
Jiahan Zhang |
|
WE-FG-DBRA-4: Knowledge-based Treatment Planning
Full Automation of Head-And-Neck Contouring, VMAT Planning, and Independent Plan Checks |
Rachel McCarroll |
|
WE-FG-DBRA-7: Knowledge-based Treatment Planning
Modeling of Multiple Planning Target Volumes (PTVs) in Knowledge-Based Planning (KBP) |
Jiahan Zhang |
|
WE-FG-DBRA-10: Knowledge-based Treatment Planning
Fully Automated Configuration of An Algorithm for Automated Multi-Objective Treatment Planning |
Rens van Haveren |
|
WE-FG-DBRA-11: Knowledge-based Treatment Planning
Knowledge-Based Treatment Planning Increases Complexity and Reduces Delivery Accuracy of VMAT Plans for Prostate Cancer |
Phillip Wall |
|
WE-HI-DBRA-10: Particle Therapy Optimization and Planning
Planning Strategies for Linear Energy Transfer Reduction in Structures with Suspected Treatment Related Toxicities Following Proton Therapy for Brain Tumors |
Jakob Ödén |
|
| Ensuring Safety, Quality, and Efficiency |
WE-AB-KDBRB1-9: Novel Imaging Modalities and Applications
HINGE - A Demonstration of FHIR Framework Principles Into An Integrated Health Care Platform for Quality Assessment, Analytics and Smart Decision-Support Apps in Radiation Oncology |
Joseph Nalluri |
|
WE-J-KDBRA1-7: Patient Safety and Quality Improvement
Treatment Planning System Beam Modeling Parameters Exhibit High Variation Among Radiotherapy Institutions |
Mallory Glenn |
|
WE-FG-KDBRA1-8: New QA and Dosimetry Techniques
Independent Recalculation Outperforms Traditional Measurement-Based IMRT QA Methods in Detecting Unacceptable Plans |
Stephen Kry |
|
WE-J-KDBRA1-6: Patient Safety and Quality Improvement
Statistical Shape Models for the Automated Detection of OAR Segmentation Abnormalities |
Eduard Schreibmann |
|
WE-J-KDBRA1-3: Patient Safety and Quality Improvement
Electronic Whiteboard Program for Improving Efficiency of Treatment Planning Workflow |
Hungcheng Chen |
|
WE-AB-DBRA-10: Brachytherapy and Radionuclide Therapy
Streamlined HDR Skin Brachytherapy with Optical 3D Scanning, 3D Printing and Augmented Reality |
Christian Guthier |
|
| Precision in Treatment Delivery |
WE-AB-DBRA-4: Brachytherapy and Radionuclide Therapy
Dose Measurements and Monte Carlo Simulations of a Directional LDR Brachytherapy Source Array |
Manik Aima |
|
WE-AB-DBRA-11: Brachytherapy and Radionuclide Therapy
Biodistribution and Pharmacokinetic Analysis of a Targeted Alpha Particle Therapy |
Christopher Tichacek |
|
WE-FG-KDBRA1-3: New QA and Dosimetry Techniques
Adapting 3D Printer Technology for QA of Gammaknife Icon High Definition Motion Management System |
Kevin Grantham |
|
WE-HI-DBRA-3: Particle Therapy Optimization and Planning
An Automated Planning Strategy for Near Real-Time Adaptive Proton Therapy |
Thyrza Jagt |
|
WE-HI-DBRA-9: Particle Therapy Optimization and Planning
Robust Optimization for Intensity-Modulated Proton Therapy to Redistribute High Linear Energy Transfer From Organs at Risk to Tumors in Head and Neck Cancer |
Chenbin Liu |
|
| New Approaches to Quantify Dose |
WE-FG-KDBRA1-1: New QA and Dosimetry Techniques
Absolute Dosimetry Using a Novel Portable Water Calorimeter Design in MR-Linac |
Humza Nusrat |
|
WE-FG-KDBRA1-2: New QA and Dosimetry Techniques
Accuracy of Real-Time Large and Small Beam Measurements From An MR-Linac Using Cherenkov Imaging Technique in a Water Tank |
Jacqueline Andreozzi |
|
WE-FG-KDBRA1-5: New QA and Dosimetry Techniques
Cherenkov Emission-Based Photon and Electron Beam Dosimetry |
Yana Zlateva |
|
WE-FG-KDBRA1-7: New QA and Dosimetry Techniques
First Characterization of a Novel Reusable Radiochromic Film for QA and Dose Measurement |
Cielle Collins |
|
| MRI in RT |
WE-FG-KDBRB1-6: MRI Guided Radiation Therapy
BEST IN PHYSICS (JOINT IMAGING-THERAPY): On Axis and X-Band Linac Designs Enable Improved Passive Magnetic Shielding in MRI-Linac Systems |
Brendan Whelan |
|
WE-FG-KDBRB1-8: MRI Guided Radiation Therapy
Deep Learning for Head and Neck Segmentation in MR: A Tool for the MR-Guided Radiotherapy |
Brian Anderson |
|
WE-FG-KDBRB1-9: MRI Guided Radiation Therapy
Electron Return Effect Predictions From Treatment Planning System of An MR-Linac Underestimate the Observations Seen Using Scintillation and Cherenkov Optical Imaging |
Jacqueline Andreozzi |
|
WE-FG-KDBRB1-10: MRI Guided Radiation Therapy
Model-Interpolated Gating for MRI-Guided Radiotherapy |
John Ginn |
|
WE-HI-KDBRB1-7: Tracking and Motion Management
Volumetric Cine MRI (VC-MRI) Using Motion Modeling, Free-Form Deformation and Multi-Slice Undersampled 2D Cine MRI Reconstructed with Spatio-Temporal Low-Rank Decomposition |
Wendy Harris |
|
WE-J-KDBRC-6: QA for Advanced Imaging Applications
Novel Phantom and Optical Imaging Technique Can Co-Align Magnetic Resonance Imaging and Radiation Isocenters for Integrated Therapy Systems |
Jacqueline Andreozzi |
|
| Real-Time Treatment Guidance |
WE-AB-DBRA-7: Brachytherapy and Radionuclide Therapy
It Is About (real) Time to Verify HDR Treatments: Duke Solution Using Nano-Fiber Optic Detector |
Michelle Rokni |
|
WE-AB-KDBRB1-1: Novel Imaging Modalities and Applications
Compton Scatter Imaging for Lung SBRT Assessed Through Phantom Studies |
Kevin Jones |
|
WE-AB-KDBRB1-7: Novel Imaging Modalities and Applications
Cherenkov Imaging for Total Skin Electron Therapy (TSET) |
Yunhe Xie |
|
WE-FG-KDBRA1-4: New QA and Dosimetry Techniques
BEST IN PHYSICS (THERAPY): 4D Dynamic Robotic Phantom System for Patient-Specific Quality Assurance in Real Time Tumor Tracking Radiotherapy |
Takehiro Shiinoki |
|
WE-HI-KDBRB1-2: Tracking and Motion Management
Characterisation of 4D Ultrasound Systems with Streaming Interfaces for Real-Time Motion Compensation in Radiotherapy |
Svenja Ipsen |
|
WE-HI-KDBRB1-3: Tracking and Motion Management
High Accuracy Estimation of Real-Time Six Degrees of Freedom (6DoF) Intrafraction Tumor Motion with Intermittent KV Imaging by Incorporating External Respiratory Signal |
Doan Trang Nguyen |
|
WE-HI-KDBRB1-4: Tracking and Motion Management
Predicting Real-Time 3D Deformation Field Maps (DFM) Based On Volumetric Cine MRI (VC-MRI) and Artificial Neural Networks for On-Board 4D Target Tracking/Gating |
Wendy Harris |
|
WE-HI-KDBRB1-11: Tracking and Motion Management
Real-Time Localization of Intrafractional Lung Tumor Motion Using IR-UWB Radars |
Raghed El-Bardan |
|
| Response Assessment |
WE-AB-KDBRC-3: Longitudinal and Functional Imaging
Investigation of Dose-Correlated MR Biomarker Changes in Brain Metastases Post-SRS |
Jeff Winter |
|
WE-AB-KDBRC-5: Longitudinal and Functional Imaging
Multiparametric Regional Radiation Dose-Response of Normal Lung On Longitudinal MAA-SPECT/CT and FDG-PET/CT Imaging of FLARE-RT Protocol Patients |
Hannah Thomas |
|
WE-AB-KDBRC-7: Longitudinal and Functional Imaging
Comparison of Regional Lung Perfusion Response On Longitudinal MAA SPECT/CT in Lung Cancer Patients Treated with and Without Functional Lung Avoidance Radiation Therapy |
Hannah Thomas |
|
| Prediction and Classification |
WE-AB-202-4: Magnetic Resonance Imaging
Complementary Value of MRI-Radiomics Features and Molecular Biomarkers in Glioblastoma to Predict Overall Survival |
Florent Tixier |
|
WE-AB-202-8: Magnetic Resonance Imaging
Preoperative Prediction of Early Recurrence in Intrahepatic Cholangiocarcinoma After Partial Hepatectomy |
Lei Xu |
|
WE-AB-KDBRC-6: Longitudinal and Functional Imaging
BEST IN PHYSICS (JOINT IMAGING-THERAPY): Variogram-Weighted Generalized Least Squares Regression to Predict Spatially Variant Tumor Voxel Response On Longitudinal FDG-PET/CT Imaging of FLARE-RT Protocol Patients |
Stephen Bowen |
|
WE-AB-KDBRC-10: Longitudinal and Functional Imaging
Predicting Lung Tumor Shrinkage During Radiotherapy Seen in a Longitudinal MR Imaging Study Via a Deep Learning Algorithm |
chuang wang |
|
WE-FG-DBRA-5: Knowledge-based Treatment Planning
Head and Neck Salivary Gland Spatial Dose-Volume Histogram (DVH) Patterns Predict Radiation-Induced Xerostomia, From Injury to Recovery |
Peijin Han |
|
| Artificial Intelligence and Machine Learning |
WE-AB-KDBRC-10: Longitudinal and Functional Imaging
Predicting Lung Tumor Shrinkage During Radiotherapy Seen in a Longitudinal MR Imaging Study Via a Deep Learning Algorithm |
chuang wang |
|
WE-FG-207-3: Computed Tomography II
Deep Learning for Automated Quantification of Tumor Phenotypes |
Ahmed Hosny |
|
WE-FG-KDBRB1-8: MRI Guided Radiation Therapy
Deep Learning for Head and Neck Segmentation in MR: A Tool for the MR-Guided Radiotherapy |
Brian Anderson |
|
WE-HI-KDBRB1-4: Tracking and Motion Management
Predicting Real-Time 3D Deformation Field Maps (DFM) Based On Volumetric Cine MRI (VC-MRI) and Artificial Neural Networks for On-Board 4D Target Tracking/Gating |
Wendy Harris |
|
| Novel Detection Technologies |
TH-CD-207-6: Radiography and Fluoroscopy
How Does Anti-Charge Sharing Impact the Zero-Frequency DQE of Photon Counting Detector Systems? Theoretical Framework and Experimental Validation |
Xu Ji |
|
TH-EF-202-2: Cone-beam Computed Tomography
A Novel High Quantum Efficiency MV X-Ray Detector for Image-Guided Radiotherapy |
Jian Liu |
|
| Re-Imagining CT Methodology |
TH-AB-202-7: Multienergy Computed Tomography
Multi-Energy CT for Multi-Phase Imaging Using Two Contrast Agents: Does It Reduce Radiation Dose? |
Liqiang Ren |
|
TH-AB-202-9: Multienergy Computed Tomography
Noise Suppression in Image-Domain Material Decomposition for Triple-Energy CT |
Shanzhou Niu |
|
TH-EF-202-3: Cone-beam Computed Tomography
BEST IN PHYSICS (IMAGING): Prospective Control of Prior-Image-Based Reconstruction for Ultralow-Dose CT: Application in Lung Nodule Surveillance |
Hao Zhang |
|
| Artifact and Noise Mitigation |
TH-EF-202-9: Cone-beam Computed Tomography
Noise Subtraction for CT Images Acquired at Multiple Dose Levels Using a Deep Convolutional Neural Network |
Andrew Missert |
|
TH-EF-202-4: Cone-beam Computed Tomography
CBCT Projection-Domain Scatter Correction with a Residual Convolutional Neural Network |
Yusuke Nomura |
|
| Intelligent Treatment Planning |
TH-AB-KDBRA1-4: Novel Treatment Delivery and Verification Strategies
A Novel Method to Facilitate Optimization of VMAT-Based Total Marrow Irradiation Plans with the Knowledge-Based Treatment Planning Technique |
Chunhui Han |
|
TH-AB-KDBRC-6: Adaptive Radiation Therapy
Integrating Virtual Bronchoscopy with Ventilation Mapping for Preserving Post-Treatment Respiratory Function in Lung Stereotactic Ablative Radiotherapy |
Esther Vicente |
|
| Informing Therapy with Biology |
TH-AB-KDBRA1-6: Novel Treatment Delivery and Verification Strategies
A Preclinical Study of Combination Therapy Using Radiation Therapy with 5-Aminolevulinic Acid and Carbamide Peroxide |
Joseph Panetta |
|
TH-AB-KDBRA1-12: Novel Treatment Delivery and Verification Strategies
Radiotherapy with No Margins |
Wilfred Ngwa |
|
TH-CD-DBRA-10: Radiation Dosimetry and Quality Assurance
Macro-To-Micro Modeling and Dosimetry for the Salivary Gland: Application to 131I and 225Ac-PSMA Therapy |
Robert Hobbs |
|
TH-EF-KDBRA1-10: Monte Carlo Simulation and High Performance Computing
Monte Carlo Simulation of the Dose From Radiosynoviorthesis Using Sn-117m, Er-169, and Re-186 Including Stochastic Macrophage Motion |
Aashish Gupta |
|
| Ensuring Safety, Quality, and Efficiency |
TH-AB-DBRA-11: Treatment Implications of Motion Management
Novel Visual Feedback Device Provides Enhanced Patient Coaching Experience for Patients Undergoing Left Breast DIBH |
David Campos |
|
TH-AB-KDBRB1-9: Point/Counterpoint Live Debate: Artificial Intelligence Will Soon Change the Landscape of Medical Physics Research and Practice
Using Machine Learning to Develop a Novel Error Detection Algorithm for HDR Brachytherapy |
David Sterling |
|
TH-AB-KDBRC-7: Adaptive Radiation Therapy
BEST IN PHYSICS (JOINT IMAGING-THERAPY): Avoiding Highly Functional Ventilation Zones Decreases the Risk of Radiation Pneumonitis During Proton and Photon Radiotherapy for Lung Cancer |
Shannon O'Reilly |
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| Precision in Treatment Delivery |
TH-AB-DBRA-2: Treatment Implications of Motion Management
An Externally and Internally Deformable Lung Motion Phantom with Programmable, Variable External-Internal Correlation |
maida ranjbar |
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TH-AB-KDBRA1-1: Novel Treatment Delivery and Verification Strategies
4piVMAT for Efficient Delivery of Highly Conformal Non-Coplanar Plans |
Qihui Lyu |
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TH-AB-KDBRA1-11: Novel Treatment Delivery and Verification Strategies
Simultaneous MLC and Couch Tracking: A Clinical Feasibility Study |
Lei Zhang |
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TH-EF-KDBRA1-7: Monte Carlo Simulation and High Performance Computing
Experimental Verification of 4D Monte Carlo Simulations in a Deforming Anatomy |
Sara Gholampourkashi |
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TH-EF-KDBRA1-8: Monte Carlo Simulation and High Performance Computing
GPU-Accelerated Optimization of Biologically Effective Dose for Inverse-Planned Nonuniform Spatio-Temporal Fractionation |
Aaron Hagan |
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| New Approaches to Quantify Dose |
TH-CD-DBRA-9: Radiation Dosimetry and Quality Assurance
Fiber Optic Dosimeters Based On Silver-Only Coated Hollow Waveguides for Radiation Therapy Dosimetry |
Arash Darafsheh |
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TH-EF-KDBRA1-5: Monte Carlo Simulation and High Performance Computing
Distributed Multi-GPU Photon Beamlet Dose Calculation for Efficient Radiation Treatment Planning |
Ryan Neph |
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| MRI in RT |
TH-AB-KDBRA1-8: Novel Treatment Delivery and Verification Strategies
Performance of a Doubly-Focused Double-Stack Multi-Leaf Collimator (MLC) System On a MR Guided Linear Accelerator |
Bin Cai |
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TH-EF-KDBRB1-9: MRI in Treatment Planning
Patient-Specific Synthetic CT Generation for MRI-Only Prostate Radiotherapy Treatment Planning |
Xiaofeng Yang |
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| Prediction and Classification |
TH-AB-DBRA-7: Treatment Implications of Motion Management
Impact of Parotid Gland Migration On Xerostomia Prediction |
Rosario Astaburuaga |
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TH-AB-DBRB-4: Radiomics (Session 5 of the Certificate Series)
A Multi-Objective Based Feature Selection Method for Lung Nodule Malignancy Classification |
Zhiguo Zhou |
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TH-AB-KDBRB1-6: Point/Counterpoint Live Debate: Artificial Intelligence Will Soon Change the Landscape of Medical Physics Research and Practice
Lung Nodule Malignancy Prediction by Combining Handcrafted Features and Deep Convolutional Neural Network |
Shulong Li |
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| Artificial Intelligence and Machine Learning |
TH-AB-KDBRB1-5: Point/Counterpoint Live Debate: Artificial Intelligence Will Soon Change the Landscape of Medical Physics Research and Practice
Super-Resolution 1H Magnetic Resonance Spectroscopic Imaging Utilizing Deep Learning |
Zohaib Iqbal |
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TH-AB-KDBRB1-6: Point/Counterpoint Live Debate: Artificial Intelligence Will Soon Change the Landscape of Medical Physics Research and Practice
Lung Nodule Malignancy Prediction by Combining Handcrafted Features and Deep Convolutional Neural Network |
Shulong Li |
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TH-AB-KDBRB1-7: Point/Counterpoint Live Debate: Artificial Intelligence Will Soon Change the Landscape of Medical Physics Research and Practice
A Deep Learning-Based Tumor Auto-Contouring Algorithm for Real-Time Tumor Tracking Using Linac-MR |
Jihyun Yun |
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TH-AB-KDBRB1-9: Point/Counterpoint Live Debate: Artificial Intelligence Will Soon Change the Landscape of Medical Physics Research and Practice
Using Machine Learning to Develop a Novel Error Detection Algorithm for HDR Brachytherapy |
David Sterling |
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TH-CD-207-2: Radiography and Fluoroscopy
Deep Learning in the Classification of Thoracic Radiographic Views to Enable Accurate and Efficient Clinical Workflows |
Jennie Crosby |
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TH-CD-KDBRC-8: Registration and Segmentation
Atrous Convolution and Spatial Pyramid Pooling for More Accurate Tumor Segmentation in MR Images |
Kuo Men |
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TH-CD-KDBRC-9: Registration and Segmentation
A Deep Learning Based Auto Segmentation for H&N Organs On Treatment Planning CT Images |
Shijun Sun |
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TH-EF-202-9: Cone-beam Computed Tomography
Noise Subtraction for CT Images Acquired at Multiple Dose Levels Using a Deep Convolutional Neural Network |
Andrew Missert |
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TH-EF-202-4: Cone-beam Computed Tomography
CBCT Projection-Domain Scatter Correction with a Residual Convolutional Neural Network |
Yusuke Nomura |
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TH-EF-KDBRB1-9: MRI in Treatment Planning
Patient-Specific Synthetic CT Generation for MRI-Only Prostate Radiotherapy Treatment Planning |
Xiaofeng Yang |
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