Lung Segmentation Model

This release contains the trained Lung Segmentation model. Details can be found in the documentation here.

What's Changed

• ENH: Improve rtconvert log visibility by @peterhessey in #814
• DOC: Correct RTD version by @peterhessey in #815
• DOC: Fix doc typo by @peterhessey in #820
• ENH: Publish lung segmentation model by @peterhessey in #808
• DOC: Hotfix doc links by @peterhessey in #823

Full Changelog: v0.7...v0.8

v0.7: Amulet compatibility and DICOM-RT fixes

What's Changed

• DOC: Typo fix by @sarthakpati in #803
• ENH: Fix logging + model registration for Amulet runs by @peterhessey in #804
• ENH: Upgrade DICOM-RT Version to 1.1.0 by @peterhessey in #807

New Contributors

• @sarthakpati made their first contribution in #803

Full Changelog: v0.6...v0.7

v0.6 Docs + Security Patches

What's Changed

• DOC: Improve hippocampus model documentation by @mebristo in #772
• DEL: Delete empty grad cam file by @mebristo in #775
• DOC: Update installation guide in /docs/WSL.md by @arsenkhy in #769
• ENH: Move docs folder to sphinx-docs by @peterhessey in #768
• DOC: Add all InnerEye/ML docstrings to ReadTheDocs by @peterhessey in #783
• DOC: Add a copy of the software dev document from hi-ml by @ant0nsc in #789
• ENH: Switch recommonmark to MyST-parser by @peterhessey in #787
• BUG: Dont update multi-node env vars for single node training by @mebristo in #796
• DOC: Add AML notes for how ACR is used by @ktakeda1 in #795
• DOC: Add scripts to RTD by @peterhessey in #793
• DOC: Add InnerEye/Azure docstrings to RTD by @peterhessey in #788
• DOC: Add InnerEye/Common docstrings to RTD by @peterhessey in #797
• DOC: Fix dead TRE links by @peterhessey in #798
• ENH: Upgrading package versions for security patches by @peterhessey in #757

New Contributors

• @arsenkhy made their first contribution in #769

Full Changelog: v0.5...v0.6

Hippocampus segmentation model

Hippocampus segmentation model v0.1

Details and instructions here:
https://github.com/microsoft/InnerEye-DeepLearning/blob/v0.5/docs/hippocampus_model.md

Environment locking, bug fixes, stability improvements + various other changes.

What's Changed

• Correct path for ensemble models by @JonathanTripp in #472
• Fix for SDK regression bug, minor doc updates by @ant0nsc in #475
• Set l_rate correctly and ensure no overlap between subjects in dataset splits in CovidHierarchicalModel config by @Shruthi42 in #467
• Update documentation for submodules by @ant0nsc in #481
• Multi-node checkpoint recovery fix by @melanibe in #478
• Check bool parameter is either true or false (after lower) by @JonathanTripp in #482
• Better handling of missing seriesId by @JonathanTripp in #488
• Minor bug fixes in CovidHierarchicalModel by @Shruthi42 in #490
• Better handling of outliers by @JonathanTripp in #489
• Fix for stuck test set inference for LightningContainer models by @ant0nsc in #494
• Regression test coverage for AzureML runs by @ant0nsc in #492
• Bug fix for regression test by @ant0nsc in #496
• Remove 2 files that cause PR build to fail non-reproducibly by @ant0nsc in #500
• Fix timeouts when downloading multiple checkpoint files by @ant0nsc in #498
• Reduce AML snapshot size by skipping test folders by @ant0nsc in #497
• Use best epoch for model comparison by @JonathanTripp in #495
• Fix bug in all_azure_dataset_ids and all_dataset_mountpoints by @Shruthi42 in #466
• Allow cross validation with 'bring your own' Lightning models (without ensemble building) by @dumbledad in #483
• Comment out glaucoma job by @JonathanTripp in #520
• Split validation and test infer config by @JonathanTripp in #502
• Added ability to run segmentation inference module in the test data without or partial ground truth files. by @asantamariapang in #465
• Partial ground truth inference PR (465) missed two things by @dumbledad in #522
• Enable store_dataset_sample by @javier-alvarez in #525
• Better Ensemble Child Inference Defaults by @JonathanTripp in #533
• Update PL to 1.3.8 by @melanibe in #531
• Update README.md by @ktakeda1 in #511
• Fixes for mounting and matplotlib problems by @ant0nsc in #515
• Dropping windows tests, but keeping cred-scan by @dumbledad in #542
• Run inference using checkpoints from registered models by @Shruthi42 in #509
• Enable a disabled test by @ant0nsc in #536
• Print warning if inference is disabled but comparison requested by @JonathanTripp in #537
• Update to fix issues in daily build by @ant0nsc in #545
• Update Covid configs by @Shruthi42 in #526
• Environment and hello_world_model documentation updated by @vale-salvatelli in #546
• Fix: pl_find_unused_parameters was no longer used by @ant0nsc in #547
• Minor changes to CovidModel config parameters and updated report by @Shruthi42 in #554
• Fix incomplete test data module setup in Lightning inference by @dccastro in #553
• Moving InnerEye's Azure code to hi-ml package by @ant0nsc in #548
• Fix learning rate parameter in SSLContainer by @Shruthi42 in #557
• Use SSLEncoder when building model in CovidModel config by @Shruthi42 in #558
• Generalize SSL functionality to work on other datasets by @vale-salvatelli in #555
• Adding Active Label Cleaning code by @melanibe in #559
• Update environment.yml to hi-ml-azure>=0.1 by @dccastro in #566
• Updating pillow to fix component governance issue by @vale-salvatelli in #567
• Adding pre-commit hooks and black formatting by @vale-salvatelli in #560
• Adjust to new namespaces by @ant0nsc in #572
• Document Segmentation Model Evaluation by @JonathanTripp in #544
• Remove the stdout.txt file by @ant0nsc in #576
• Switching batch time loading diagnostics to hi-ml by @ant0nsc in #577
• Update hello_world_model.md by @maxilse in #580
• Fix for AzureML environment problem by @ant0nsc in #587
• Enable overriding AzureConfig parameters from a LightningContainer by @dccastro in #589
• Fix for invalid path_on_compute problem by @ant0nsc in #593
• Fixing SSL recovery, attempt 2 by @ant0nsc in #584
• Use PIL.PngImagePlugin to load pngs by @JonathanTripp in #588
• Make pytorch run non-deterministically by default, upgrade to AML SDK 1.36 by @ant0nsc in #594
• Add cudatoolkit=11.1 to environment.yml by @dccastro in #596
• Add histopathology module and add hi-ml as submodule by @mebristo in #603
• Add --pl_deterministic to build training jobs by @dccastro in #605
• Bug fix: deployed models and training code use different versions of hi-ml by @ant0nsc in #606
• Bug fix: When using local folders, datasets are downloaded nevertheless by @ant0nsc in #604
• Mebristo/move histopathology update by @mebristo in #613
• Downloading checkpoints from AML if not found on disk by @ant0nsc in #614
• Enabling distributed training for SSL online evaluator by @ant0nsc in #612
• Add more histopathology configs by @mebristo in #616
• Small cleanups for checkpoint loading by @ant0nsc in #615
• Simplify setting callbacks in LightningContainers by @ant0nsc in #617
• Adding pipeline cache for conda environment by @ant0nsc in #618
• Vsalva/deepmil panda by @vale-salvatelli in #619
• Upgrade to Pytorch Lightning 1.5.5 by @ant0nsc in #591
• Bug fix: multi-GPU jobs on a VM use wrong folders by @ant0nsc in #622
• Enable tiling non-PANDA WSI datasets by @dccastro in #621
• Bug fix: SSL on multiple nodes used wrong LR scheduler by @ant0nsc in #628
• SSL Online evaluator: save checkpoints without DDP wrapper by @ant0nsc in #623
• Upgrade to PyTorch 1.10 by @ant0nsc in #585
• Moving *.nii.gz from git lfs to git to simplify the HelloWorld test by @ant0nsc in #632
• fixing PandaInnereyeSSLMIL by @vale-salvatelli in #625
• Improve recovery of preempted jobs by @ant0nsc in #633
• Plotting heatmap and thumbnails for test PANDA slides by @harshita-s in https://github.com/microsoft/InnerEye-DeepLearnin...

Support for bring-your-own-model, self-supervised learning and fastMRI

The biggest new features in this release are

• A framework to train any PyTorch-Lightning model with InnerEye toolbox
• Training self-supervised models
• Support for multi-node training in AzureML
• Extending the InnerEye toolbox so that it works for the models from the fastMRI challenge
  Full details are in CHANGELOG.md

Migrate to PyTorch Lightning

This release contains the switch to PyTorch Lightning, plus various small fixes as per changelog.

Baseline

This is the baseline release, including all changes up to 2020-11-13.