Machine Learning in MRI: From Methods to Clinical Translation Volume 13 (Paperback)

1. Basics of machine learningTypes of learning: Supervised, self-supervised, semi-supervised, active learning, reinforcement learning
2. MR image acquisitionActive scanning, sequence parameter optimization
3. MR image reconstructionDL reconstruction
4. MR motion correctionPairwise image registration
5. MR image post-processingImage segmentation
6. Generalization and fairnessAI fairness and bias, domain adaptation
7. Publicly available codes, databases and challenges
8. Clinical translation/application(outcome, treatment prediction, patient monitoring, image quality