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Keywords: Noise
MO-C930-IePD-F8-2Two 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
MO-I430-BReP-F1-4How Accurate Is in Vivo Noise Estimation From Patient CT Images? Validation of Methods Against Ensemble Noise Gold Standard
F Ria1,2,3,*, H Setiawan2,3, E Abadi2,3, J Solomon1,2,3,, E Samei1,2,3, (1) Clinical Imaging Physics Group Duke University Health Systems, Durham, NC, (2) RAI Labs Duke University, Durham, NC, (3) Center for Virtual Imaging Trials Duke University, Durham, NC
PO-GePV-M-186Quantitative Evaluation and Feasibility Study of Using AI Denoising Technique to Minimize Image Dose of 2.5MV Beam
H Kuo1*, S Lim1, S Lin2, J Sillanpaa1, L Cervino1, (1) Memorial Sloan Kettering Cancer Center, New York, NY (2) Norwalk Hospital, Norwalk, CT
SU-E-207-1Noise2noise Deep Learning Based Acceleration for MRI Echo-Planar Imaging
L Qin1*, C Lindsay2, A Konik1, G Young3, (1) Dana-Farber Cancer Institute, Boston, MA, (2) University Of Massachusetts Chan Medical School, Worcester, MA (3) Brigham And Women's Hospital, Boston, MA
SU-F-201-7Discriminability 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-202-5Use of Automation in Image Quality Analysis in PET
T Moretti*, S Leon, C Schaeffer, M Arreola, University of Florida, Gainesville, FL
TH-A-206-4Quantifying Robustness of CT-Ventilation Biomarkers to Image Noise
M Flakus1*, A Wuschner2, E Wallat3, J Meudt4, D Shanmuganayagam5, G Christensen6, J Reinhardt7, J Bayouth8, (1) University of Wisconsin, Madison, WI, (2) University of Wisconsin, Madison, WI, (3) University of Wisconsin, Madison, WI, (4) ,Madison, WI, (5) ,Madison, WI, (6) University of Iowa, Iowa City, IA, (7) University of Iowa, Iowa City, IA, (8) University of Wisconsin-Madison, Madison, WI
TH-B-207-2Motion-Compensated Quantitative Digital Subtraction Angiography (qDSA) in Noisy Image Sequences
J Whitehead*, S Periyasamy, C Hoffman, P Laeseke, M Speidel, M Wagner, University of Wisconsin - Madison, Madison, WI
TH-D-201-1Comprehensive 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
TH-D-207-6Texture Transformer Super-Resolution (TTSR) for Patient CT Images
S Zhou1*, L Yu2, M Jin1, (1) University of Texas at Arlington, Arlington, TX, (2) Mayo Clinic, Rochester, MN
WE-A-201-4Joint K-B Space Image Reconstruction and Data Fitting for Diffusion-Weighted Magnetic Resonance Imaging
J Deng*, X Jia, The University of Texas Southwestern Medical Ctr, Garland, TX
WE-G-201-4Improved Spectral Imaging with More Energy Bins for Realistic Photon Counting Detectors
A Wang1*, Y Yang1, S Wang1, Z Yin2, (1) Stanford University, Stanford, CA, (2) GE Healthcare