diff --git a/documentation/bids.rst b/documentation/bids.rst index 67b8aa4af..3d4afe216 100644 --- a/documentation/bids.rst +++ b/documentation/bids.rst @@ -5,7 +5,7 @@ BIDS and BIDS App standards ******************************************* -``MIALSRTK BIDS App`` adopts the :abbr:`BIDS (Brain Imaging Data Structure)` standard for data organization and is developed following the BIDS App standard. This means that ``MIALSRTK BIDS App`` handles dataset formatted following the BIDS App standard and provides a processing workflow containerized in Docker container image (promoting portability and reproduciblity) that can be run with a set of arguments defined by the BIDS App standard directly from the terminal or a script (See :ref:`cmdusage` section for more details). +`MIALSRTK BIDS App` adopts the :abbr:`BIDS (Brain Imaging Data Structure)` standard for data organization and is developed following the BIDS App standard. This means that `MIALSRTK BIDS App` handles dataset formatted following the BIDS App standard and provides a processing workflow containerized in Docker container image (promoting portability and reproduciblity) that can be run with a set of arguments defined by the BIDS App standard directly from the terminal or a script (See :ref:`cmdusage` section for more details). For more information about BIDS and BIDS-Apps, please consult the `BIDS Website `_, the `Online BIDS Specifications `_, and the `BIDSApps Website `_. `HeuDiConv `_ can assist you in converting DICOM brain imaging data to BIDS. A nice tutorial can be found @ `BIDS Tutorial Series: HeuDiConv Walkthrough `_ . @@ -46,7 +46,7 @@ The BIDS App accepts BIDS datasets that adopt the following organization, naming code/ participants_params.json -where ``participants_params.json`` is the MIALSRTK BIDS App configuration file, which following a specific schema (See :ref:`config schema `), and which defines multiple processing parameters (such as the ordered list of scans or the weight of regularization). +where ``participants_params.json`` is the MIALSRTK BIDS App configuration file, which follows a specific schema (See :ref:`config schema `), and which defines multiple processing parameters (such as the ordered list of scans or the weight of regularization). .. important:: Before using any BIDS App, we highly recommend you to validate your BIDS structured dataset with the free, online `BIDS Validator `_. diff --git a/documentation/contributing.rst b/documentation/contributing.rst index d7e19e731..63d1833a6 100644 --- a/documentation/contributing.rst +++ b/documentation/contributing.rst @@ -95,7 +95,7 @@ Before you submit a pull request, check that it meets these guidelines: How to build the BIDS App locally ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -1. Go to the clone directory of your fork and run the script ``build_bidsapp.sh`` :: +1. Go to the clone directory of your fork and run the script `build_bidsapp.sh` :: cd mialsuperresolutiontoolkit sh build_bidsapp.sh @@ -107,27 +107,27 @@ Note that the tag of the version of the image will be extracted from ``pymialsrt How to build the documentation locally ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -1. Install the MIALSRTK conda environment ``pymialsrtk-env`` with sphinx and all extensions to generate the documentation:: +1. Install the `MIALSRTK` conda environment `pymialsrtk-env` with sphinx and all extensions to generate the documentation:: cd mialsuperresolutiontoolkit conda env create -f docker/bidsapp/environment.yml -2. Activate the MIALSRTK conda environment ``pymialsrtk-env`` and install ``pymialsrtk`` :: +2. Activate the MIALSRTK conda environment `pymialsrtk-env` and install `pymialsrtk` :: conda activate pymialsrtk-env python setup.py install -3. Run the script ``build_sphinx_docs.sh`` to generate the HTML documentation in ``documentation/_build/html``:: +3. Run the script `build_sphinx_docs.sh` to generate the HTML documentation in ``documentation/_build/html``:: bash build_sphinx_docs.sh .. note:: - Make sure to have activated the conda environment ``pymialsrtk-env`` before running the script ``build_sphinx_docs.sh``. + Make sure to have activated the conda environment `pymialsrtk-env` before running the script `build_sphinx_docs.sh`. Not listed as a contributor? ---------------------------- -This is easy, MIALSRTK has the `all contributors bot `_ installed. +This is easy, `MIALSRTK` has the `all contributors bot `_ installed. Just comment on Issue or Pull Request (PR), asking `@all-contributors` to add you as contributor:: diff --git a/documentation/index.rst b/documentation/index.rst index f28e0fa51..f92772c81 100644 --- a/documentation/index.rst +++ b/documentation/index.rst @@ -45,9 +45,9 @@ Introduction The `Medical Image Analysis Laboratory Super-Resolution ToolKit (MIALSRTK)` consists of a set of C++ and Python3 image processing and worflow tools necessary to perform motion-robust super-resolution fetal MRI reconstruction. -The *original* `C++ MIALSRTK library` includes all algorithms and methods for brain extraction, intensity standardization, motion estimation and super-resolution. It uses the CMake build system and depends on the open-source image processing Insight ToolKit (ITK) library, the command line parser TCLAP library and OpenMP for multi-threading. +The *original* `C++ MIALSRTK` library includes all algorithms and methods for brain extraction, intensity standardization, motion estimation and super-resolution. It uses the CMake build system and depends on the open-source image processing Insight ToolKit (ITK) library, the command line parser TCLAP library and OpenMP for multi-threading. -MIALSRTK has been extended with the `pymialsrtk` Python library following recent advances in standardization of neuroimaging data organization and processing workflows (See :ref:`BIDS and BIDS App standards `). This library has a modular architecture built on top of the Nipype dataflow library which consists of (1) processing nodes that interface with each of the MIALSRTK C++ tools and (2) a processing pipeline that links the interfaces in a common workflow. +`MIALSRTK` has been extended with the `pymialsrtk` Python3 library following recent advances in standardization of neuroimaging data organization and processing workflows (See :ref:`BIDS and BIDS App standards `). This library has a modular architecture built on top of the Nipype dataflow library which consists of (1) processing nodes that interface with each of the MIALSRTK C++ tools and (2) a processing pipeline that links the interfaces in a common workflow. The processing pipeline with all dependencies including the C++ MIALSRTK tools are encapsulated in a Docker image container, which is now distributed as a `BIDS App` which handles datasets organized following the BIDS standard. See :ref:`BIDS App usage ` for more details. @@ -56,7 +56,7 @@ All these design considerations allow us not only to (1) represent the entire pr Aknowledgment -------------- -If your are using the MIALSRTK BIDS App in your work, please acknowledge this software and its dependencies. See :ref:`Citing ` for more details. +If your are using `MIALSRTK` in your work, please acknowledge this software and its dependencies. See :ref:`Citing ` for more details. License information -------------------- diff --git a/documentation/outputs.rst b/documentation/outputs.rst index dbe5618b1..64221bd88 100644 --- a/documentation/outputs.rst +++ b/documentation/outputs.rst @@ -25,7 +25,7 @@ BIDS derivatives entities See `Original BIDS Entities Appendix `_ for more description. -.. note:: A new entity ``id-