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Keywords: Noise Reduction
MO-IePD-TRACK 1-7Impact 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-M-154Impact of Various Noise Reduction Techniques On Markerless Tumor Tracking in Dual Energy Imaging
M Kaur1*, P Wagstaff1, H Mostafavi2, M Lehmann2, D Morf2, L Cortesi2, L Zhu2, H Kang1, M Harkenrider1, J Roeske1, (1) Loyola University, Chicago, IL, (2) Varian Medical Systems, Palo Alto, CA
TH-E-TRACK 5-1A Feasibility Study for Deep Learning-Based Efficient Monte Carlo Dose Calculation Method in Radiotherapy
X Lu1*, Y Li2, Q Mengke1, L Zhou1, T Song1, (1)Department of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, CN, (2)Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, CN
TH-IePD-TRACK 1-4Dose Savings and Image Quality in Dual-Energy Non-Contrast CT Scans
G Anthony*, Y Liang, Indiana University, Indianapolis, IN
TH-IePD-TRACK 2-6Need for a Saturation RF Band to Mitigate Flow Artifact in 3D-MPRAGE On a Compact 3T Scanner
M In*, N Campeau, J Huston, D Kang, L Bardwell Speltz, N Meyer, J Trzasko, Y Shu, M Bernstein, Mayo Clinic, Rochester, MN
TU-D-TRACK 3-6Task-Based Loss Function for Convolutional Neural Network-Based CT Denoising
B Nelson1*, D Gomez Cardona2, N Huber1, A Missert1, L Yu1, C McCollough1, (1) Mayo Clinic, Rochester, MN, (2) Gundersen Health System, La Crosse, WI
TU-D-TRACK 3-7Evaluation of Image-Domain Training Frameworks for Deep Learning Based Denoising and Deconvolution
P VanMeter1*, S Hsieh1, J Marsh1, N Huber1, A Ferrero1, C McCollough1, (1) Department of Radiology, Mayo Clinic, Rochester, MN
WE-IePD-TRACK 2-4Global Noise Analysis of Single and Dual Source CT for Obese Patients
MA Thomas*, M Ahmad, MC Jacobsen, N Wagner-Bartak, C Jensen, RR Layman, UT MD Anderson Cancer Center, Houston, TX