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|MO-C930-IePD-F8-2||Two Vendor-Specific Deep Learning Iterative Reconstruction Algorithms (DLIR) for CT Were Assessed for Image Quality Impact Towards Dose Reduction Feasibility|
S Brady1*, (1) Cincinnati Childrens Hospital Med Ctr, Mason, OH
|SU-F-201-7||Discriminability of Non-Gaussian Noise Properties in CT and the Limitation of the Noise Power Spectrum to Describe Noise Texture|
K Boedeker1*, D Shin2, L Oostveen3, I Sechopoulos4, C Abbey5, (1) Canon Medical Systems Corporation, Otawara, Japan (2) (1) Canon Medical Systems Corporation, Otawara, Japan (3) Radboud University Nijmegen Medical Centre, Nijmegen, ,NL, (4) Radboud University Medical Centre, Nijmegen, ,(5) University of California - Santa Barbara, Santa Barbara, CA
|SU-F-202-5||Use of Automation in Image Quality Analysis in PET|
T Moretti*, S Leon, C Schaeffer, M Arreola, University of Florida, Gainesville, FL
|TH-D-201-1||Comprehensive Size- and Kernel-Dependent Comparison of Image Quality Between Photon-Counting and Energy Integrating CT|
M Bhattarai1*, S Bache2, E Abadi1 E Samei1,2, (1) Duke University, Durham, NC, (2) Duke University Health System, Durham, NC