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Classroom Contents
Geometric Understanding of Supervised and Unsupervised Deep Learning for Biomedical Image Reconstruction
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- 1 Intro
- 2 Veep Learning for Image Reconstruction Diagnosis & analysis
- 3 Deep Learning Revolution for Inverse Problem
- 4 Classical Methods for Inverse Problems
- 5 Input Space Partitioning for Multiple Expressions
- 6 Lipschitz Continuity
- 7 Regularized Recon vs. Deep Recon
- 8 Ultrasound Acquisition Modes
- 9 Adaptive Beamformer
- 10 Image Domain Learning is Essential?
- 11 Two Approaches for CT Reconstruction
- 12 DBP Domain ROI Tomography
- 13 DBP Domain Conebeam Artifact Removal
- 14 Style Transfer : Power of Tight Frame U-net
- 15 Our Penalized LS Formulation
- 16 Unsupervised Blind Deconvolution Microscopy
- 17 Unsupervised Learning for Accelerated MRI
- 18 Summary
