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Keywords: Radiography
| MO-IePD-TRACK 1-1 | Using Exposure Index to Develop Thickness-Based Techniques for the Skull Views of a Pediatric Skeletal Survey X Li1*, K Hulme1, E Park1, (1) Imaging Institute, Cleveland Clinic, Cleveland, OH |
| MO-IePD-TRACK 1-2 | Development of a Size-Based Technique Chart for Portable Chest Images to Reduce Variability in Image Quality J Moroz*, M Hoerner, K Grizzard, Yale New Haven Health, New Haven, CT |
| MO-IePD-TRACK 1-3 | A Novel Integrating Proton Radiography System with a Monolithic Scintillator Detector C Darne1*, D Robertson2, F Alsanea3, I Tendler4, L Perles5, C Collins-Fekete6, S Beddar7, (1) UT MD Anderson Cancer Center, Houston, TX, (2) Mayo Clinic Arizona, Phoenix, AZ, (3) UT MD Anderson Cancer Center, Houston, TX, (4) UT MD Anderson Cancer Center, Houston, TX, (5) UT MD Anderson Cancer Center, Houston, TX, (6) University College London, London, GB, (7) UT MD Anderson Cancer Center, Houston, TX |
| MO-IePD-TRACK 1-7 | Impact of Flexible Noise Control (FNC) Processing Parameters On Image Quality: A Chest Phantom Study L Ren*, T Daly, K Loewen, B Schueler, Z Long, Mayo Clinic, Rochester, MN |
| PO-GePV-I-23 | Conformance Analysis Between Positive Beam Limitation Quality Control Methods in Digital Roentgen-Ray Imaging R Perez Franco*, M Fadhel, D Vergara, A Mustafa, I Bercha, Yale New Haven Hospital, Yale School of Medicine, New Haven, CT |
| PO-GePV-M-17 | Prediction of WEPL Image in Proton Radiography Using Deep Learning Alaka B G1*, D Samuel2, E Bentefour3, (1) Central University of Karnataka, Kalaburgi, Karnataka, IN, (2) Central University Of Karnataka, ,,(3) University of Maryland School of Medicine, Baltimore. |
| PO-GePV-M-41 | Automatic Lung Field Segmentation On Chest Radiographs of COVID-19 Patients to Improve Diagnostic Deep Learning G Schlafly*, Q Hu, F Li, K Drukker, J Fuhrman, M Giger, University of Chicago, Chicago, IL |
| SU-CD-TRACK 3-0 | Medical Imaging and Data Resource Center: Imaging in Covid M Giger1*, P Kinahan2*, M McNitt-Gray3*, K Myers4*, S Armato5*, (1) University of Chicago, Chicago, IL, (2) University of Washington, Seattle, WA, (3) David Geffen School of Medicine at UCLA, Los Angeles, CA, (4) Office of Science and Engineering Laboratories, FDA, Silver Spring, MD, (5) The University of Chicago, Chicago, IL |
| SU-IePD-TRACK 1-3 | Self-Supervised Deep Learning in the Assessment of Enteral Feeding Tube Positioning Based On A Small Dataset G Liang1*, D Steffey2, H Ganesh3, J Zhang4, (1) Eastern Kentucky University, ,,(2) University Of Kentucky, ,,(3) University Of Kentucky, ,,(4) University of Kentucky, Lexington, KY |
| SU-IePD-TRACK 1-5 | Multi-Frequency-Based CXR Data Normalization for Deep-Neural-Network Classifier H Kim*, KAIST, Daejon, KR, W Sim, Radisen, Seoul, KR, D Cho, Radisen, Seoul, KR, S Cho, KAIST, Daejeon, KR |
| TU-B-TRACK 6-2 | Model-Based Reconstruction for Proton CT Detected with Multiple-Layer Ionization Chamber X Chen*, B Sun, Y Hao, F Reynoso, A Darafsheh, D Yang, T Zhang, T Zhao, Washington University School of Medicine, St. Louis, MO |
| TU-IePD-TRACK 4-3 | Integrated Structure Name Mapping with CNN P Bose1*, W Sleeman2, S Srinivasan3, J Palta4, R Kapoor5, P Ghosh6, (1) Virginia Commonwealth University,Richmond, VA, (2) Virginia Commonwealth University, Richmond, VA, (3) Virginia Commonwealth University,Richmond, VA, (4) Virginia Commonwealth University, Richmond, VA, (5) VCU Health System, Richmond, VA, (6) Virginia Commonwealth University, Richmond, VA, |
| WE-IePD-TRACK 4-4 | Assessment of Clinical to High Energy Proton Radiography Viability Using TOPAS B Broder1*, M Freeman2, (1) University of Chicago, Chicago, IL, (2) Los Alamos National Laboratory, Los Alamos, NM |