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Change Log

All notable changes to this project will be documented in this file. It's a team effort to make them as straightforward as possible.

The format is based on Keep a Changelog and this project adheres to Semantic Versioning.

[1.0.0-rc1] - In Progress

Release comment: refactoring of models means that old checkpoint files are no longer compatible with the updates.

Added

  • Added num_parallel_calls option in config for data preprocessing.
  • Added tests for Dice score, Jaccard Index, and cross entropy losses.
  • Added statistics on inputs, DDF and TRE into tensorboard.
  • Added example for using custom loss.
  • Added tests on Mac OS.
  • Added tests for python 3.6 and 3.7.
  • Added support to custom layer channels in U-Net.
  • Added support to multiple loss functions for each loss type: "image", "label" and "regularization".
  • Added LNCC computation using separable 1-D filters for all kernels available

Changed

  • Updated pre-trained models for unpaired_ct_abdomen demo to new version
  • Changed dataset config so that format and labeled are defined per split.
  • Reduced TensorFlow logging level.
  • Used DEEPREG_LOG_LEVEL to control logging in DeepReg.
  • Increased all EPS to 1e-5.
  • Clarify the suggestion in doc to use all-zero masks for missing labels.
  • Moved contributor list to a separate page.
  • Changed no-test flag to full for demo scripts.
  • Renamed neg_weight to background_weight.
  • Renamed log_dir to exp_name and log_root to log_dir respectively.
  • Uniformed local-net, global-net, u-net under a single u-net structure.
  • Simplified custom layer definitions.
  • Removed multiple unnecessary custom layers and use tf.keras.layers whenever possible.
  • Refactored BSplines interpolation independently of the backbone network and available only for DDF and DVF models.

Fixed

  • Fixed using GPU remotely
  • Fixed LNCC loss regarding INF values.
  • Removed loss weight checks to be more robust.
  • Fixed import error under python 3.6.
  • Fixed the residual module in local net architecture, compatible for previous checkpoints.
  • Broken link in README to seminar video.

[0.1.2] - 2021-01-31

Release comment: This is mainly a bugfix release, although some of the tasks in 1.0.0-rc1 have been included in this release, with or without public-facing accessibility (see details below).

Added

  • Added global NCC loss
  • Added the docs on registry for backbone models.
  • Added backward compatible config parser.
  • Added tests so that test coverage is 100%.
  • Added config file docs with details on how new config works.
  • Added DDF data augmentation.
  • Added the registry for backbone models and losses.
  • Added pylint with partial check (C0103,C0301,R1725,W0107,W9012,W9015) to CI.
  • Added badges for code quality and maintainability.
  • Added additional links (CoC, PyPI) and information (contributing, citing) to project README.md.
  • Added CMIC seminar where DeepReg was introduced to the project README.md.
  • Added deepreg_download entry point to access non-release folders required for Quick Start.

Changed

  • Refactored optimizer configuration.
  • Refactored affine transform data augmentation.
  • Modified the implementation of resampler to support zero boundary condition.
  • Refactored loss functions into classes.
  • Use CheckpointManager callback for saving and support training restore.
  • Changed distribute strategy to default for <= 1 GPU.
  • Migrated from Travis-CI to GitHub Actions.
  • Simplified configuration for backbone models and losses.
  • Simplified contributing documentation.
  • Uniform kernel size for LNCC loss.
  • Improved demo configurations with the updated pre-trained models for: grouped_mask_prostate_longitudinal, paried_mrus_prostate, unpaired_us_prostate_cv, grouped_mr_heart, unpaired_ct_lung, paired_ct_lung.

Fixed

  • Fixed several dead links in the documentation.
  • Fixed a bug due to typo when image loss weight is zero, label loss is not applied.
  • Fixed warp CLI tool by saving outputs in Nifti1 format.
  • Fixed optimiser storage and loading from checkpoints.
  • Fixed bias initialization for theta in GlobalNet.
  • Removed invalid first argument in DataLoader for sample_index generator.
  • Fixed build error when downloading data from the private repository.
  • Fixed the typo for CLI tools in documents.

[0.1.0] - 2020-11-02

Added

  • Added option to change the kernel size and type for LNCC image similarity loss.
  • Added visualization tool for generating gifs from model outputs.
  • Added the max_epochs argument for training to overwrite configuration.
  • Added the log_root argument for training and prediction to customize the log file location.
  • Added more meaningful error messages for data loading.
  • Added integration tests for all demos.
  • Added environment.yml file for Conda environment creation.
  • Added Dockerfile.
  • Added the documentation about using UCL cluster with DeepReg.

Changed

  • Updated TensorFlow version to 2.3.1.
  • Updated the pre-trained models in MR brain demo.
  • Updated instruction on Conda environment creation.
  • Updated the documentation regarding pre-commit and unit-testing.
  • Updated the issue and pull-request templates.
  • Updated the instructions for all demos.
  • Updated pre-commit hooks version.
  • Updated JOSS paper to address reviewers' comments.
  • Migrated from travis-ci.org to travis-ci.com.

Fixed

  • Fixed prediction error when number of samples cannot be divided by batch size exactly.
  • Fixed division by zero handling in multiple image/label losses.
  • Fixed tensor comparison in unit tests and impacted tests.
  • Removed normalization of DDF/DVF when saving in Nifti formats.
  • Fixed invalid link in the quick start page.

[0.1.0b1] - 2020-09-01

Initial beta release.