| Tuesday |
TU-AB-202-2: Breast Imaging
BEST IN PHYSICS (IMAGING): Evaluation of An Automated Grid Artifact Detection System for Quality Control in Digital Mammography |
Christopher MacLellan |
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TU-AB-202-4: Breast Imaging
Back-Projection Filtration Image Reconstruction Approach for Reducing High-Density Object Artifacts in Digital Breast Tomosynthesis |
Hyeongseok Kim |
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TU-AB-202-9: Breast Imaging
Reconstruction Algorithm Design for Mitigating the Orientation Dependent Conspicuity of Fiber-Like Signals in Digital Breast Tomosynthesis |
Sean Rose |
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TU-K-DBRB-3: Quantitative Imaging: CT and MRI
Application and Performance Evaluation of a Modified BM3D Denoising Method to Emphysema Scoring On Ultra-Low-Dose CT Images |
Tingting Zhao |
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| Wednesday |
WE-AB-KDBRB1-6: Novel Imaging Modalities and Applications
BEST IN PHYSICS (JOINT IMAGING-THERAPY): ACROBEAT: Adaptive CaRdiac COne BEAm Computed Tomography |
Tess Reynolds |
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WE-FG-207-4: Computed Tomography II
Automated-Adaptive Iterative Metal Artifact Reduction: Quantitative Evaluation of Streak Artifact Reduction When Reconstructing CT Images in Presence of Metal |
Nilesh Mistry |
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| Thursday |
TH-EF-202-9: Cone-beam Computed Tomography
Noise Subtraction for CT Images Acquired at Multiple Dose Levels Using a Deep Convolutional Neural Network |
Andrew Missert |
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TH-EF-202-4: Cone-beam Computed Tomography
CBCT Projection-Domain Scatter Correction with a Residual Convolutional Neural Network |
Yusuke Nomura |
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