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Taxonomy: IM/TH- Cone Beam CT: Quantitative Imaging
| BReP-SNAP-I-19 | Estimation of Tumor Tracer Kinetics Employing a Novel Cross Voxel Exchange Model N Sinno1*, E Taylor1, M Milosevic1, D Jaffray2, C Coolens1 (1) Princess Margaret Cancer Centre, Toronto, ON, (2) UT MD Anderson Cancer Center, Houston, TX |
| BReP-SNAP-I-28 | Integrated Intensity-Based Quantification of Small Airway Dimensions Using Computed Tomography Y Zhao, S Molloi*, University of California-Irvine, Irvine, CA |
| BReP-SNAP-I-34 | Noise Power Spectrum Analysis E mckenzie*, D Gauntt, UAB Medical Center, Birmingham, AL |
| BReP-SNAP-M-65 | Evaluation of a Localized Correlation Based Predictive Metric as a Decision Making Tool in Online Image Guidance and Offline Adaptive Prostate Radiotherapy A Gopal*, B Zhang, G Lasio, S Lee, B Yi, Univ. of Maryland School Of Medicine, Baltimore, MD |
| BReP-SNAP-M-81 | High-Precision Dosimetry in Yttrium-90 Radioembolization Through Post-Procedural CT Imaging of Radiopaque Microspheres in a Porcine Model C Henry1*, M Strugari1,2, G Mawko1,3,4,6, K Brewer1,2,5,R Abraham4,7, A Syme1,3,6, (1) Department of Physics, Dalhousie University, Halifax, NS, CA, (2) Biomedical Translational Imaging Centre (BIOTIC), Halifax, NS, CA, (3) Department of Medical Physics, Nova Scotia Health Authority, Halifax, NS, CA, (4) Department of Diagnostic Imaging and Interventional Radiology, Dalhousie University, Halifax, NS, CA, (5) Department of Biomedical Engineering, Dalhousie University, Halifax, NS, CA, (6) Department of Radiation Oncology, Dalhousie University, Halifax, NS, CA, (7) ABK Biomedical Inc., Halifax, NS, CA |
| BReP-SNAP-M-108 | Off-Line Treatment Monitoring of Head and Neck Radiotherapy Using Daily Cone-Beam Computed Tomography: A Preliminary Study S Lee1*, B Zhang1, G Lasio1, A Gopal1, I Lee2, H Xu1, S Chen1, B Yi1, (1) University of Maryland School of Medicine, Baltimore, MD, (2) University of Maryland, College Park, MD |
| BReP-SNAP-M-135 | Simplification of Transmission Factor Determination for I-131 Gamma Camera Based Internal Dosimetry with Co-57 Solid Flood Source Q Liang1*, L Chen2, R Klein3, J Halama4, R Harvey5, J Schwartz6, D Fisher7, (1) Actinium Pharmaceuticals, New York, NY, (2) Banner MD Anderson Cancer Center, Gilbert, AZ, (3) The Ottawa Hospital, Ottawa, ON, Canada, (4) Loyola Univ Medical Center, Maywood, IL, (5) Roswell Park Cancer Institute, Buffalo, NY, (6) Memorial Sloan Kettering Cancer Center, New York, NY, (7) Versant Medical Physics And Radiation Safety, Richland, WA |
| MO-E-TRACK 2-4 | Experimental Comparison of Particle Vs Photon Imaging for Relative Stopping Power Prediction E Baer1*, L Volz2, C-A Collins-Fekete1, S Brons3, A Runz4, R Schulte5, J Seco2, (1) University College London, London, GB, (2) Biomedical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, DE, (3) Heidelberg Ion Beam Therapy Center (HIT), Heidelberg, DE, (4) Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany, (5) Loma Linda University, Loma Linda, CA, USA, (2) Medical Physics in Radiation Oncology, German Cancer Research Center, Heidelberg, DE |
| MO-F-TRACK 1-6 | Automated Quantification of Spatially Abnormal 129-Xe MRI Ventilation and Perfusion: Implications for Lung Cancer, Asthma, and COPD Interventions M Mcintosh*, R Eddy, J Macneil, A Matheson, G Parraga, Robarts Research Institute, Western University, London, ON, CA |
| PO-GeP-I-10 | A Method for Assessing Confidence of Dual-Contrast Photon-Counting CT Material Quantification C Leary*, T Griglock, Oregon Health & Science Univ, Portland, OR |
| PO-GeP-I-13 | A Novel Linear Model for Quantitative Magnetic Resonance Imaging Based On Spin Echo Sequence: A Feasibility Study S Li*, Y Zhang, H Wu#, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, Beijing, BeijingCN, #corresponding author: Hao Wu; email: hao.wu@bjcancer.org |
| PO-GeP-I-24 | Accurate 3D Stopping-Power Ratio Estimation by Statistical Image Reconstruction From Dual Energy CT Sinogram Data Exported From a Commercial Multi-Slice CT Scanner M Medrano1*, T Ge1, D Politte2, J Williamson2, T Zhao2, R Liu2, R Liao1, M Porras-Chaverri4, B Whiting3, J O'Sullivan 1 (1) Washington University in St. Louis, St. Louis, MO,(2) Washington University School of Medicine, St. Louis, MO, (3) University of Pittsburgh, Pittsburgh, PA, (4) Universidad de Costa Rica, San Jose, SJ |
| PO-GeP-I-37 | Automated ACR Image Analysis for MR Imaging for All Seven Tests C Burton*, Boston Children's Hospital, Boston, MA |
| PO-GeP-I-48 | Characterization of Liver and Pancreatic Tumor Motion Using Real-Time Planar Cine MR Images D Gunasekara1*, J Darko1, E Osei1, B Maraghechi2, T Mazur2, H Li2, (1) Grand River Regional Cancer Center, Kitchener, ON, CA, (2) Washington University School of Medicine, St. Louis, MO, USA |
| PO-GeP-I-58 | Comparison of Image Noise in Dual Energy CT Images Reconstructed Using Filtered Back-Projection, Hybrid Iterative Reconstruction, and Deep Learning Methods P Prakash*, B Nett, J Tang, GE Healthcare Technologies, Waukesha, WI |
| PO-GeP-I-62 | Compatibility Evaluation of Dose Modulations Among Various CT Scanners J James1*, G Anthony2, Y Liang3, (1) Indiana University, Imaging Sciences, Indianapolis, IN, (2) Indiana University, Imaging Sciences, Indianapolis, IN, (3) Indiana University, Imaging Sciences, Indianapolis, IN |
| PO-GeP-I-143 | Inter-Scanner T1 and T2 Mapping Evaluation Using Multiple MRI Phantoms at 3T J Yu*, S Fahrenholtz, Y Zhou, W Sensakovic, A Panda, Mayo Clinic, Phoenix, AZ |
| PO-GeP-I-161 | Optimization of [18F]FDG Injected Activity for a New GE Discovery MI PET/CT Scanner Using a NEMA Phantom A Hart1*, T O'Briain1, M Bazalova-Carter1, A Rahmim2,3, W Beckham1,3, C Uribe-munoz4, (1) University of Victoria, Victoria, BC, CA, (2) University of British Columbia, Vancouver, BC, CA, (3) BC Cancer, Victoria, BC, (4) BC Cancer, Vancouver, BC, CA |
| PO-GeP-I-175 | Quantification of Small Airway Dimensions Using High Resolution Computed Tomography: A Phantom Study Y Zhao1*, A Hernandez2, J Boone2,3, S Molloi1, (1) University of California-Irvine, Irvine, CA, (2) University of California-Davis, Sacramento, CA, (3) UC Davis Medical Center, Sacramento, CA |
| PO-GeP-I-186 | Reducing CSF Contamination in Cortical T2 Using a Fluid-Suppressed Dual-Echo Pulse Sequence R Gabr1*, M Yang2, P Narayana1, (1) University of Texas Health Science Center at Houston, Houston, TX, (2) Texas A&M University, College Station, TX |
| PO-GeP-I-199 | Study On the Influence of Lung Cancer Target Delineation with Different SUV Thresholds On Feature Extraction in 18F-FDG-PET Images C Ma*, Shandong Cancer Hospital and Institute,Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, N/ACN, |
| PO-GeP-I-221 | Tumor-Specific 99mTc-Sestamibi Quantification in Molecular Breast Imaging with Monte Carlo Simulation B Lopez*, F Guan, G Rauch, S Kappadath, University of Texas MD Anderson Cancer Center, Houston, TX, USA |
| PO-GeP-M-93 | Characterization of CT Hounsfield Units Uniformity of 3D-Printed Materials for Proton Therapy E Orton1*, C Engelberts1, R Orbovic1, M Crocker1,2, B Basaric1, D Sobczak3, L Zhao3, (1) Adaptiiv Medical Technologies, Halifax, NS, CA, (2) Dalhousie University, Halifax, NS, CA, (3) St. Jude Children's Research Hospital, Memphis, TN |
| PO-GeP-M-126 | CT Image Parameter Estimation Using PCA-Based Deep Learning in Chronic Obstructive Pulmonary Disease A Moslemi1*, W Tan2, J Bourbeau3, J Hogg2, H Coxson2, M Kirby1, (1) Ryerson University, Toronto, Ontario, CA, (2) Centre For Heart Lung Innovation, University Of British Columbia, (3) McGill University |
| PO-GeP-M-192 | Evaluating ICBCT Image Quality at Halcyon Linac for Patient Set Up Verification M Gei1*, J Visak2, D Pokhrel3, (1) University of Kentucky, Georgetown, KY, (2) University of Kentucky, New Lenox, IL, (3) University of Kentucky, Lexington, KY |
| 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 Qiu1*, J Duan1, H Deng2, Z Han3, J Gu1, Y Yin1, (1) Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, CN, (2) Second Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu, CN (3) Yantai Yuhuangding Hospital, Yantai, Shandong, CN |
| SU-B-TRACK 2-1 | BEST IN PHYSICS (MULTI-DISCIPLINARY): Parameters for In-Vivo Quantitative Ultrasound Evaluation of Subresolution Scattering Sources in Carotid Atherosclerotic Plaque C Steffel*, S Salamat, S Wilbrand, R Dempsey, C Mitchell, T Varghese, University of Wisconsin-Madison, Madison, WI |
| SU-B-TRACK 2-5 | A Quantitative Analysis of Lung Elastography Using Free Breathing Fast Helical CT Scans B Stiehl*, M Lauria, I Barjaktarevic, D Low, A Santhanam, UCLA, Los Angeles, CA |
| SU-F-TRACK 1-5 | Determination of in Vivo Tissue Optical Properties for Anal PDT A Li*, Y Ong, T Busch, TC Zhu, University Pennsylvania, Philadelphia, PA |
| TH-AB-TRACK 4-10 | Lung Functional Avoidance Radiotherapy: Characterizing Spatial Differences Between Ventilation and Perfusion F Forghani1*, T Patton1, D Thomas1, Q Diot1, C Rusthoven1, R Castillo2, E Castillo3, I Grills3, T Guerrero3, M Miften1, Y Vinogradskiy1, (1) University of Colorado Anschutz Medical Campus, Aurora, CO (2) Emory Univ, Atlanta, GA, (3) Beaumont, Royal Oak, MI |
| TU-C-TRACK 1-6 | Motion Artifact Impact On Dose Calculation Using CBCT S Scheib1*, I Peterlik2, P Paysan3, S Scheib4, Varian Medical Systems Imaging Laboratory, Daettwil Ag, CH, |
| TU-CD-TRACK 2-6 | Quantitative Characterization of Tumor Proximity to Stem Cell Niches: Implications On Recurrence and Survival in GBM Patients Y Lao1*, A Pham2, T Wang2, J Cui2, H Gallogly2, E Chang2, Z Fan3, K Sheng1, W Yang2, (1) UCLA School of Medicine, Los Angeles, CA (2) Univ Southern California, Los Angeles, CA (3) Cedars-Sinai Medical Center, Los Angeles, CA |
| TU-EF-TRACK 1-0 | Quantitative Ultrasound Imaging: From Benchtop to a Clinical Protocol T Hall1*, J Fowlkes2*, M Averkiou3*, J Mamou4*, I Rosado-Mendez5*, (1) University of WI-Madison/ADCL, Madison, WI, (2) University Michigan Health Systems, Ann Arbor, MI, (3) University of Washington, Seattle, WA, (4) Riverside Research Institute, New York, NY, (5) Universidad Nacional Autonoma de Mexico, Mexico, MX |
| WE-D-TRACK 1-1 | Predicting Net 90Y Administered Activity in 90Y-Radioembolization From Post-Therapy 90Y-SPECT/CT Images M. Allan Thomas1*, Benjamin P. Lopez1, Adam Neff3, Armeen Mahvash2, S. Cheenu Kappadath1, (1) Department of Imaging Physics, UT MD Anderson Cancer Center, Houston, TX, (2) Department of Interventional Radiology, UT MD Anderson Cancer Center, Houston, TX, (3) MIM Software, Inc., Cleveland, OH |
| WE-E-TRACK 2-5 | Correlation Between Hematocrit and Blood CT Number Changes During Radiation Therapy X Chen*, H Saeed, X Li, Medical College of Wisconsin, Milwaukee, WI |
| WE-E-TRACK 2-7 | Phenotyping Potential of Topologically Invariant Betti Numbers for Epidermal Growth Factor Receptor Mutations in Non-Small Cell Lung Cancer Patients K Ninomiya1*, H Arimura1, W Chan2, K Tanaka3, S Mizuno1, N Muhammad Gowdh2, N Yaakup2, C Liam2, C Chai4, K Ng2, (1)Kyushu University, (2)University Of Malaya, (3)Kyushu University Hospital, (4) University Malaysia Sarawak |
| WE-F-TRACK 1-6 | Annotation-Efficient Deep Learning for Free Breathing Proton Magnetic Resonance Imaging Segmentation D Capaldi1*, F Guo2, T Nano3, O Morin4, L Xing5, G Parraga6, (1) Stanford University, Stanford, CA, (2) Sunnybrook Research Institute, (3) University of California, San Franisco, San Francisco, CA, (4) University of California San Francisco, San Francisco, CA, (5) Stanford Univ School of Medicine, Stanford, CA, (6) Western University, London, ON, CA |