clinicadl - v2.0.0rc1

[2.0.0rc1] – 2025-07-24

This release marks a major overhaul of ClinicaDL, refactoring the entire framework into a modular, API-first design.

Previously centered around the command line, ClinicaDL now provides a flexible Python API that allows users to build and customize deep learning pipelines with high-level configuration objects. The goal is to make the code more maintainable, scalable, and user-extensible, while preserving the core values of ClinicaDL: reproducibility, robust support for neuroimaging, and data leakage prevention.

This is the first release candidate for version 2.0.0, with the final release planned for September 2025.

Highlights

• Full rewrite of the core library — now fully object-oriented and modular.
• New modules (see next section)
• New MAPS architecture for managing model outputs and metadata.
• Clear configuration-based design with JSON files and dedicated config classes based on pydantic.
• Modern deep learning tooling: PyTorch, MONAI, TorchIO, HuggingFace, MLflow, and Weights & Biases support.
• Extensive and fully updated documentation.

Added

Core Modules:

• Trainer: high-level training controller managing full model lifecycle.
• ClinicaDLModel: flexible base class to define and extend custom architectures.
• CapsDataset: redesigned dataset class in the new dataset module, tailored for CAPS/MAPS.
• Splitter: new module for managing train/val/test split logic.
• Maps: a structured and reproducible representation of model outputs and metadata.

Configuration Classes:

• OptimizationConfig, DataloaderConfig, LossConfig, TransformConfig, MetricConfig, etc.
• Designed to be composable and readable using TOML files.
• Stored alongside results to ensure experiment traceability.

Integration with Modern Tools:

• Transforms: use of torchio and monai.transforms for preprocessing and data augmentation.
• Metrics: integration with MONAI metrics and support for custom metrics.
• Networks: fully compatible with native PyTorch models.
• Logging: support for MLflow and Weights & Biases (W&B) out of the box.
• HuggingFace: integration point for loading pretrained models and tokenizers.

Documentation:

• Fully rewritten Sphinx documentation with improved structure and usage examples.
• Interactive object documentation and visual MAPS structure navigation.

Changed

• All pipelines removed and replaced by a unified API-driven interface.
• Internal architecture redesigned for independent modules that can be combined or extended.
• CLI options replaced by TOML configuration — reducing duplication and increasing clarity.
• All training now done through Trainer, using configuration objects and custom hooks.

Removed

• All legacy CLI commands (e.g., clinicadl train, clinicadl random-search, etc.).
• Old pipelines (train_from_json, preprocessing run, etc.).
• JSON-based configuration files.
• Hardcoded command-line flags and argparse logic.

Breaking Changes

• Backward compatibility is broken with all 1.x versions.
• You must migrate to the new API and TOML-based configuration system.

- Python
Published by camillebrianceau 7 months ago

clinicadl - ClinicaDL v1.6.1

ClinicaDL 1.6.1

Fixed

• Fix sorting particpants sessions with 2 digit,
• Fix interpret —-save_nifti issue,
• Fix BIDS file format for pet,

Changed

• Change 2 digits session label to 3 digits,
• Change black and isort for ruff and codespell,
• Update type hint and docstring,

New

• Add --fsdp option
• Add --valid_longitudinal option to allow the validation on longitudinal data,

- Python
Published by camillebrianceau almost 2 years ago

clinicadl - ClinicaDL v1.6.0

- Python
Published by camillebrianceau about 2 years ago

clinicadl - ClinicaDL v1.5.1

ClinicaDL 1.5.1

Fixed

• Fix retrocompatibility for new option in maps.json

Changed

• Change MapsManager architecture by adding Callbacks

New

• Add --fully_sharded_data_parallelism option
• Add --emisions_calculator option with codecarbon
• Add the semi-supervised domain adaptation network proposed for the MICCAI DART workshop.

- Python
Published by camillebrianceau over 2 years ago

clinicadl - ClinicaDL v1.5.0

ClinicaDL 1.5.0

### Fixed

• Fix adapt command

### Changed

• SSIM is now executed on GPU when possible

### New

• Add new command generate artifacts to generate noise/contract/motion
• Add options for data augmentation
• Add fine-tuning option
• Add --amp for automatic mixed precision
• Add --track_exp option to track your parameters during training with MLflow or WandB

- Python
Published by camillebrianceau over 2 years ago

clinicadl - ClinicaDL v1.4.0

Fixed

• Fix --diagnoses and --merged_tsv option bug in clinicadl get-labels
• Fix Pathlib bugs
• Fix get_tsv_paths function bug.
• Fix a bug for which it was impossible to use predict without specifying the splits and selection metrics.

Changed

• Changed default batch size to 8 for clinicadl predict
• Changed VAEs main class

New

• Add --n_proc option in clinicadl generate pipelines for parallelization.
• Add --split to clinicadl predict
• Add new VAE networks.
• Add pytorch function to summarize
• Add --size_reduction and --size_reduction_factor options to clinicadl train, clinicadl predict and clinicadl interpret.
• Add SSIM2D, SSIM3D metrics for VAE.
• Add --save_latent_space option to clinicadl train and clinicadl predict.
• Add clinicadl generate trvial_motion
• Add Data augmentation with torchio

- Python
Published by camillebrianceau over 2 years ago

clinicadl - Release ClinicaDL 1.3.1

## ClinicaDL 1.3.1

### Fixed

• Fix TypeError when running ClinicaDL.
• Fix --extract_json option bug in clinicadl prepare-data.
• Fix clinicadl tsvtools get-labels error finding clinica iotools missing-modalities output.

### Changed

• Changed clinicadl tsvtools get-labels output directory.

### New

• Add --caps_directory option in clinicadl tsvtools get-labels.

- Python
Published by camillebrianceau almost 3 years ago

clinicadl - Release ClinicaDL v1.3.0

ClinicaDL 1.3.0

New

• Add new command quality-check pet-linear.
• Add new command generate hypometabolic.
• Add new network architecture: Resnet3D and SqueezeExcitationCNN.
• Add flair-linear modality for prepare-data command.
• Add pytorch profiler.
• Add --save_nifti option for interpretcommand.
• Add --output_dir argument for tsvtools get-labels command

Changed

** Core: **

• Transition from os to pathlib.
• Update data CI.
• Improve maps_manager.
• Change --acq_label option for --tracer.
• Update tutorial.

- Python
Published by camillebrianceau almost 3 years ago

clinicadl - ClinicaDL 1.2.0

ClinicaDL 1.2.0

Changed

** Core: **

• Add ClinicaDL installation with pipx.
• Improve logging.
• Add method argument to the interpret command to choose between the new Grad-CAM method and the gradient method.
• Change extract command to prepare-data.
• Change output of get-labels, split and kfold commands to one TSV per split instead of one per label.
• Change tsvtool command to tsvtools.
• Change tsvtools getlabels command to tsvtools get-labels and remove the progression column in the TSV output.
• Add new commands: tsvtools get-progression, tsvtools get-metadata, tsvtools prepare-experiment (split + kfold), and tsvtools adapt.
• Update data CI.
• Add a new model for quality check

Fixed

• Fix quality-check t1-linear

- Python
Published by camillebrianceau about 3 years ago

clinicadl - ClinicaDL 1.1.1

Changed

** Core: **

• Dependencies versions were updated in order to support Python equal or greater than 3.8.
• Security updates for some dependencies.
• Include the --save_tensor and --save_nifty options into the predict sub-command (before save_tensor was also subcommand`).
• Update some paper references in the documentation.
• Add a description for the available models.
• Add the flag --model_layers to the clinicadl train list_models subcommad to visualize the model layers.

Fixed

• Fix bug when using the clinicadl train list_models command.

- Python
Published by mdiazmel over 3 years ago

clinicadl - ClinicaDL 1.1.0

Changed

Core:

• Add new VAE models for training.
• Add multiprocessing for the extract task.
• Add tests to validate resume and quality-check functionalities.
• Update minimal version for first level dependencies: clinica, scikit-learn, scikit-image.
• Add a new Makefile to the root of the repository in order to facilitate sysadmin frequent tasks. The CI script was also modified.

Command line:

• Update of the train command line: now all actions related to training (resume, list models, tasks…) are sub-commands of the command clinicadl train. Task is now a sub-command, and not an argument.
• Add command to list the available models for the training task and the details of each model.
• Add an option to the command save-tensor to save the reconstruction outputs as nifti files.
• Add command clinicadl train from_json to train again the same experiment from a JSON file generated by ClinicaDL.

Fixed

• Allow the user to choose the optimizer and the metric independently of the performed task.
• Logger does not display output according to the --verbose option during the training tasks. This behavior is fixed.
• Behavior of resume was changed.
• Reader to request BIDS/CAPS datasets changed its interface in the recent version of Clinica (>=0.5.4). Code using these functions was adapted.
• Exceptions raised are now more specific and detailed.
• Documentation was updated.

- Python
Published by mdiazmel about 4 years ago

clinicadl - ClinicaDL 1.0.4

Changed

Core:

• Switch to Poetry to manage production and development requirements.
• Update requirements.
• Improve metrics for multi-class settings.
• Remove NaN values in input data.
• Allow to choose the name of the JSON file produced by extract.
• Improve logs.

Command line:

• Add selection_metrics option in clinicadl train (already available in TOML file).
• Print help if no argument is given.

Fixed

• Fix label code generation
• Remove all occurences of a group in a MAPS when choosing the overwriting option.
• Fix resume when the training.tsv file is empty.

- Python
Published by mdiazmel about 4 years ago

clinicadl - ClinicaDL 1.0.3

ClinicaDL 1.0.3 (release bugfix)

Fixed

• Fix import module for VAE architectures.

- Python
Published by mdiazmel over 4 years ago

clinicadl - ClinicaDL 1.0.2

ClinicaDL 1.0.2

Changed

Core:

• Clinica version dependency.
• Update documentation, with proofreading.
• Change the test for extract.

Fixed

• Use the GPU option on the command line interface.
• Fix the train task when invoking the CLI.
• Remplace the predict arguments passed through the CLI.
• Fix issue when using multiple cohorts.

- Python
Published by mdiazmel over 4 years ago

clinicadl - ClinicaDL 1.0.1

ClinicaDL 1.0.1

Changed

Functionalities:

• extract improve this functionality with more expressive and easy to understand flags.
• Change the test for extract.

Fixed

• Problem when looking for generate module when installing the package with pip.

- Python
Published by mdiazmel over 4 years ago

clinicadl - 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.

- Python
Published by mdiazmel over 4 years ago

clinicadl - ClinicaDL 0.2.2

ClinicaDL 0.2.2

Added

• New functionality clinicadl random-search analysis to obtain the histogram of the balanced accuracy over a random search folder.
• New functionality clinicadl train from_json to train a model with parameters defined in a JSON file.
• New functionality clinicadl train resume to resume a prematurely stopped training task.
• Possibility to learn the grey matter intensities with the binary classification during training, based on t1-volume outputs.
• Refactor code style using Black tool.

Changed

• Previous clinicadl random-search is now clinicadl random-search generate
• Cross-validation and computational arguments of clinicadl random-search generate are now defined in random_search.json.
• Remove tensorboardx dependency.

- Python
Published by mdiazmel over 4 years ago

clinicadl - ClinicaDL 0.2.1

ClinicaDL 0.2.1

Added

• the multi_cohort flag in train allows to train on several CAPS at the same time.

Changed

• clinicadl train roi now allows any ROI defined by a mask.
• Update README.md to avoid duplicates.
• JSON files are added for clinicadl classify and clinicadl tsvtool getlabels|split|kfold

Removed

• Scripts and data related to MedIA publication.

- Python
Published by mdiazmel almost 5 years ago

clinicadl - ClinicaDL v0.2.0

ClinicaDL v0.2.0

Added

• New functionality clinica interpret to generate saliency maps linked to pretrained models based on groups of individual images.
• New functionality clinicadl random-search to sample random networks from a predefined hyperparameter space.
• Slice subparsers for autoencoder/cnn/multicnn to be homogeneous with other parsers.
• roi parser has now multicnn option.
• Add generic options to command line: --verbose, --version and --logname.

Changed

• Behaviour of clinicadl quality-check t1-volume.
• Simplify clinicadl tsvtools behaviour when using getlabels, split and analysis.
• Update documentation.

Fixed

• Fix broken file when running preprocessing in t1-extensive.

- Python
Published by mdiazmel about 5 years ago

clinicadl - ClinicaDL v0.1.1

Changes

Core

• Add t1-extensive to the preprocessing tasks (skull-stripping of T1-weighted MR images in Ixi549Space space).

Hotfixes

• Error message when lacking information necessary to tsvtools getlabels.
• Fix some Quality Check bugs.

- Python
Published by mdiazmel over 5 years ago

clinicadl - ClinicaDL v0.1.0

Changes

Core

• New wrapper to Clinica's functions for image preprocessing and tensor extraction.
• Improve command line descriptions.
• Add and replace some options in the command line interface, mainly for the classify task.
• Add additional information to the file describing the execution environment during a task.
• Add label warning when classifying with a single class.
• Add a verbose mode to understand the stages of a specific task.

CI and tests

• New tests for tsvtool, train and generate.
• Data test available to test locally.

• Documentation was updated.

- Python
Published by mdiazmel over 5 years ago

clinicadl - ClinicaDL v0.0.3

Changes

Documentation is officially available !

- Python
Published by mdiazmel over 5 years ago

clinicadl - ClinicaDL v0.0.1

First release

This version of the code corresponds to the code used to get the results described in the scientific paper.

- Python
Published by mdiazmel over 5 years ago

clinicadl - ClinicaDL v0.0.2

Changes

CLI refactor

This release includes changes in the command line interface including: - Generation of synthetic data for functional tests. - Interface for preparing data for training. - Interface to create data (slices or patches) for training. - Command to classify an image or a group of images using previously trained models. - Reorganization of input parameter when training a new model.

- Python
Published by mdiazmel over 5 years ago

clinicadl - ClinicaDL v0.0.2b

Changes

Beta version. Preparation of release 0.0.2

- Python
Published by mdiazmel over 5 years ago