Date: December 24, 2020
This corresponds to the release of MIAL Super-Resolution Toolkit 2.0.1, that includes in particular the following changes.
- Review setup.py for publication of future release of pymialsrtk to PyPI (See `pull request 59<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/59>`_).
- Review creation of entrypoint scripts of the container for compatibility with Singularity (See `pull request 60<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/60>`_).
- Use MapNode for all interfaces that apply a processing independently to a list of images (See `pull request 68<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/68>`_).
- Use the nipype sphinx extension to generate API documentation (See `pull request 65<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/65>`_).
- Review the --manual option flag which takes as input a directory with brain masks (See `pull request 51<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/51>`_).
pymialsrtkenables to skip different steps in the super-resolution pipeline (See `pull request 63<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/63>`_).- Support of Singularity to execute MIALSTK on high-performance computing cluster (See `pull request 60<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/60>`_).
pymialsrtkimplements for convenience a Python wrapper that generates the Singularity command line of the BIDS App for you, prints it out for reporting purposes, and then executes it without further action needed (See `pull request 61<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/61>`_).
Add test-python-install job to CircleCI to test the creation of the distribution wheel to PyPI and test its installation via pip (See `pull request 34<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/34>`_).
Add deploy-pypi-release job to CircleCI to publish the package of a new release to PyPI (See `pull request 59<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/59>`_).
Add build-singularity, test-singularity, deploy-singularity-latest, and deploy-singularity-release jobs in CircleCI to build, test and deploy a Singularity image of MIALSRTK to Sylabs.io (See `pull request 34<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/34>`_). The tests includes:
- Test 03: Run BIDS App on the sample data/ BIDS dataset with the
--manual_masksoption without code coverage. - Test 04: Run BIDS App on the sample data/ BIDS dataset with automated brain extraction (masking) without code coverage.
- Test 03: Run BIDS App on the sample data/ BIDS dataset with the
Please check `pull request 53<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/53>`_ for more change details and development discussions.
Date: November 25, 2020
This corresponds to the first release of the second version of the MIAL Super-Resolution Toolkit, which has evolved massively over the last years in terms of the underlying codebase and the scope of the functionality provided, following recent advances in standardization of neuroimaging data organization and processing workflows.
- Adoption of the Brain Imaging Data Structure standard for data organization and the sample dataset available in data/ has been modified accordingly. (See :ref:`BIDS and BIDS App standards <cmpbids>` for more details)
- MIALSRTK is going to Python with the creation of the
pymialsrtkworkflow library which extends the Nipype dataflow library with the implementation of interfaces to all C++ MIALSRTK tools connected in a common workflow to perform super-resolution reconstruction of fetal brain MRI with data provenance and execution detail recordings. (See :ref:`API Documentation <api-doc>`) - Docker image encapsulating MIALSRTK is distributed as a BIDS App, a standard for containerized workflow that handles BIDS datasets with a set of predefined commandline input argument. (See :ref:`BIDS App Commadline Usage <cmdusage>` for more details)
- Main documentation of MIALSRTK is rendered using readthedocs at https://mialsrtk.readthedocs.io/.
pymialsrtkimplements an automatic brain extraction (masking) module based on a 2D U-Net (Ronneberger et al. [Ref1]) using the pre-trained weights from Salehi et al. [Ref2] (See `pull request 4<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/4>`_). It is integrated in the BIDS App workflow by default.
| [Ref1] | Ronneberger et al.; Medical Image Computing and Computer Assisted Interventions, 2015. (link to paper) |
| [Ref2] | Salehi et al.; arXiv, 2017. (link to paper) |
pymialsrtkimplements a module for automatic stack reference selection and ordering (masking) based on the tracking of the brain mask centroid slice by slice (See `pull request 34<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/34>`_)pymialsrtkimplements for convenience a Python wrapper that generates the Docker command line of the BIDS App for you,
prints it out for reporting purposes, and then executes it without further action needed (See `pull request 47<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/47>`_)
Adopt CircleCI for continuous integration testing and run the following regression tests:
- Test 01: Run BIDS App on the sample data/ BIDS dataset with the
--manual_masksoption. - Test 02: Run BIDS App on the sample data/ BIDS dataset with automated brain extraction (masking).
- Test 01: Run BIDS App on the sample data/ BIDS dataset with the
Use Codacy to support code reviews and monitor code quality over time.
Use coveragepy in CircleCI during regression tests of the BIDS app and create code coverage reports published on our Codacy project page.
Please check `pull request 2<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/2>`_, `pull request 4<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/4>`_, `pull request 34<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/34>`_, `pull request 39<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/39>`_, `pull request 47<https://github.com/Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit/pull/47>`_ for more change details and development discussions.