ClinicaDL 1.0.0

ClinicaDL 1.0.0

Welcome to ClinicaDL 1.0.0 🎉!

This is a new version of ClinicaDL with some major changes in the source code. All the main pipelines
have been refactored. ClinicaDL now used is now working with classes instead of function for easier maintenance
and better scalability. We introduce in this version our new data structure called MAPS to unify ClinicaDL outputs.

This release also include a major command line refactoring with the introduction of Click library.
Major changes in several pipelines interfaces have been implemented. For instance the preprocessing pipeline has been
split. Train pipeline has also been refactored to reduce the number of options. The goal is to make ClinicaDL more easy to use, to maintain,
and adapt the command line to the MAPS.

ClinicaDL aim for more reproducibility: some configuration files are saved in the MAPS to reproduce experiments in the same condition
(with same environnement and same parameters). In addition we added some options to fix the random processes seed and use Pytorch
latest enhancement for a deterministic behavior.

Other improvement and small fix have also been implemented.

⚠️ Be careful, this version breaks the backward compatibility with previous versions. ⚠️

Added

Pipelines:

• New extract pipeline to convert nifti images in Pytorch tensors. This pipeline now saves a preprocessing json file
  with all the information needed for the train pipeline.

Core:

• New folder structure: MAPS (Model Analysis and Processing Structure) for ClinicaDL outputs.
• New class MapsManager for MAPS to ease the interface with the MAPS: launch various tasks such as
  training and prediction, save outputs, read files...
• Other new classes to make ClinicaDL code more scalable: SplitManager, TaskManager, Network...
• Now takes pet-linear images as possible data modality.
• Possibility to fix the seed for a deterministic behavior.

Other:

• New arguments for ROI in random search.

Changed

Pipelines:

• train pipeline has now a new command line. Please see the doc for more information.
• train now accept a TOML configuration file to simplify the command line.
• train resume is now named resume.
• random-search generate is now named random-search
• random-searchnow use TOML configuration file instead of JSON.
• generate pipeline to generate synthetic dataset (random, trivial and Shepp-Logan).
• quality-check pipeline to perform quality check on Clinica t1-linear and t1-volume outputs.

Core:

• Major refactoring of the source code repository organization: now ClinicaDL core
  respects the command line hierarchy as is in Clinica repository.
• Command line: we now use Click instead of Argparse.

Other:

• Console logs enhancement.
• Replace tensorboardx dependency with torch.utils.tensorboard to remove tensorboardx from requirement.
• GitHub repository name is now ClinicaDL and not AD-DL anymore.
• We will now use GitHub discussion instead of Google Group.

Deprecated

Removed

Pipelines:

• clinicadl preprocessing pipelines have been removed. They now have new names (see above).
• clinicadl preprocessing run has now completely been removed. Please use Clinica for preprocessing.
• train_from_json pipeline has been replaced with TOML configuration file.
• clinicadl random-search analysis pipeline has been removed.

Core:

• T1-extensive preprocessing is not supported by ClinicaDL anymore.

Fixed

• Fix multi-class classification.
• Fix classification when only one ROI is given.
• Fix tsvtools when diagnosis column value is not identical to tsv file name.
• Fix clinicadl tsvtool split when n_test is 1.
• Fix ROI when user provides 3D tensor for ROI.
• Fix the use of GPU on a machine with more than on GPU (such a computer cluster).
  ClinicaDL will now select a free GPU that as permission.
• Fix an error where diagnosis column was automatically overwritten
  by the name of the file during split or kfold.