Machine Learning for Medical Image Reconstruction: 4th International Workshop, MLMIR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings

Deep Learning for Magnetic Resonance Imaging.- HyperRecon: Regularization-Agnostic CS-MRI Reconstruction with Hypernetworks.- Efficient Image Registration Network For Non-Rigid Cardiac Motion Estimation.- Evaluation of the robustness of learned MR image reconstruction to systematic deviations between training and test data for the models from the fastMRI challenge.- Self-Supervised Dynamic MRI Reconstruction.- A Simulation Pipeline to Generate Realistic Breast Images For Learning DCE-MRI Reconstruction.- Deep MRI Reconstruction with Generative Vision Transformers.- Distortion Removal and Deblurring of Single-Shot DWI MRI Scans.- One Network to Solve Them All: A Sequential Multi-Task Joint Learning Network Framework for MR Imaging Pipeline.- Physics-informed self-supervised deep learning reconstruction for accelerated rst-pass perfusion cardiac MRI.- Deep Learning for General Image Reconstruction.- Noise2Stack: Improving Image Restoration by Learning from Volumetric Data.- Real-time Video Denoising in Fluoroscopic Imaging.- A Frequency Domain Constraint for Synthetic and Real X-ray Image Super Resolution.- Semi- and Self-Supervised Multi-View Fusion of 3D Microscopy Images using Generative Adversarial Networks.

• Format: Paperback
• Language: English
• ISBN: 3030885518
• ISBN13: 9783030885519
• Release Date: September 2021
• Publisher: Springer
• Length: 142 Pages
• Weight: 0.49 lbs.
• Dimensions: 0.3" x 6.1" x 9.2"