Machine Learning for Medical Image Reconstruction

Chapter 1 Rethinking the Optimization Process for Self-supervised Model-Driven MRI Reconstruction

Chapter 2 NPB-REC: Non-parametric Assessment of Uncertainty in Deep-Learning-Based MRI Reconstruction from Undersampled Data

Chapter 3 Adversarial Robustness of MR Image Reconstruction Under Realistic Perturbations

Chapter 4 High-Fidelity MRI Reconstruction with the Densely Connected Network Cascade and Feature Residual Data Consistency Priors

Chapter 5 Metal Artifact Correction MRI Using Multi-contrast Deep Neural Networks for Diagnosis of Degenerative Spinal Diseases

Chapter 6 Segmentation-Aware MRI Reconstruction

Chapter 7 MRI Reconstruction with Conditional Adversarial Transformers

Chapter 8 A Noise-Level-Aware Framework for PET Image Denoising

Chapter 9 DuDoTrans: Dual-Domain Transformer for Sparse-View CT Reconstruction

Chapter 10 Deep Denoising Network for X-Ray Fluoroscopic Image Sequences of Moving Objects

Chapter 11 PP-MPI: A Deep Plug-and-Play Prior for Magnetic Particle Imaging Reconstruction

Chapter 12 Learning While Acquisition: Towards Active Learning Framework for Beamforming in Ultrasound Imaging

Chapter 13 DPDudoNet: Deep-Prior Based Dual-Domain Network for Low-Dose Computed Tomography Reconstruction

Chapter 14 MTD-GAN: Multi-task Discriminator Based Generative Adversarial Networks for Low-Dose CT Denoising

Chapter 15 Uncertainty-Informed Bayesian PET Image Reconstruction Using a Deep Image Prior