Self-supervised segmentation of myocardial perfusion imaging SPECT left ventricles

Project Organization

├── readme.md                      
├── experiments                             <- YAML file based configuration files to run experiments
├── notebooks                               <- Jupyter playbooks for initial experiments and code writing
├── logger.py                               <- Basic logger for Neptune.ml
├── models.py                               <- Model definitions for both SSL and supervised models
├── ssl_jigsaw_puzzle.py                    <- SSL algorithm to solve jigsaw puzzles pretext tasks
├── ssl_relative_patch_location.py          <- SSL algorithm to solve the relative patch location pretext tasks
├── supervised_training.py                  <- algorithm for supervised training on the target task after SSL
├── utils.py                                <- utility functions

Baseline method implementation

├── A new method incorporating deep learning with shape priors for left ventricular segmentation in myocardial perfusion SPECT images - https://github.com/MIILab-MTU/AIInHealthcare_LVSeg.git