v0.1.2-beta

Bug fix for the case of bad data in the analysis pipeline. We needed to reset the index in the paths data frame.

v0.1.1-beta

This release includes major changes:

1. We updated the default number of epochs to 250000/steps_per_epoch. This allows MIST to run for 250,000 optimization steps. We also validate every 250 on the entire held-out fold for cross-validation. This makes comparisons to nnUNet easier.

2. Remove the generalized dice loss (GDL), the GDL with cross-entropy loss, and remove class weights from the generalized surface loss. We have not seen any advantage to using class weights in loss functions.

3. Update documentation to include the clDice.

4. Start adding the MIST version number in the config file.

v0.1.0-beta

This release includes major changes:

1. We updated the default number of epochs to 250000/steps_per_epoch. This allows MIST to run for 250,000 optimization steps. We also validate every 250 on the entire held-out fold for cross-validation. This makes comparisons to nnUNet easier.

2. Remove the generalized dice loss (GDL), the GDL with cross-entropy loss, and remove class weights from the generalized surface loss. We have not seen any advantage to using class weights in loss functions.

3. Update documentation to include the clDice.

4. Start adding the MIST version number in the config file.

v0.0.3-beta

Update the version to get the build badge to show passing. Probably not the best way to do this, but it'll do for now. This is the same code as v0.0.2-beta.

v0.0.2-beta

Improved error handling for preprocessing and conversion tools.

Improved computation of target spacing.

v0.0.1-beta

Fix orientation issue for inference.

This was the last major bug that we needed to fix before moving from alpha to beta versions of MIST.

v0.4.20-alpha

Bug fixes for VAE regularization.

Bug fixes for pre-trained models. We know this works for nnUNet models, but we need to do more investigation.

Refactor analysis, preprocessing, inference, and training modules to production-quality code.

v0.4.19-alpha

Bug fix for evaluation.

Readability for util functions related to creating paths CSV files.

Filter out hidden files when creating train_paths.csv and fg_bboxes.csv.

Add extra error handling for small datasets and multiple GPUs.

v0.4.18-alpha

Refactor the analyze_data module to have production-quality code.

Change the back_to_original_space function in main_inference to set the predictions spacing to the target spacing before applying resampling to the original spacing.

v0.4.16-alpha

Add cldice loss function and include dynamic weighting with dice+ce loss function.

Change validation loss from dice to dice+ce.