Stanford Fullysampled 3D FSE Knees 2019 Dataset
================================================

This project folder contains the configuration files, preprocessing, and visualization scripts for the Stanford
Fullysampled 3D FSE Knees 2019 dataset.

For more information, please refer to http://mridata.org/list?project=Stanford%20Fullysampled%203D%20FSE%20Knees.

.. note::
    When running the preprocessing scripts please make sure you have the ``ismrmrd`` package installed. You can
    install it with the following command:

    .. code-block:: bash

        pip install -r requirements/requirements-ahead_stanfordknees.txt

**Visualization**
An example notebook for visualizing the data is provided in the
`visualize <https://github.com/wdika/atommic/tree/main/projects/REC/StanfordKnees2019/visualize.ipynb>`_
notebook. You just need to set the path where the dataset is downloaded.

**Preprocessing**
The preprocessing pipeline is implemented in the
`preprocess_dataset.sh <https://github.com/wdika/atommic/tree/main/projects/REC/StanfordKnees2019/preprocess_dataset.sh>`_
script, consisting of the following steps:
1. Convert the data from ``ISMRMRD`` to ``HDF5`` format.
2. Split the dataset into training and validation sets.

**Training/Testing**

.. important::
    The ``Stanford Knees`` dataset is natively supported in ``atommic``. Therefore, you do not need to create a custom
    dataset class. You just need to set the ``dataset_format`` argument in the configuration file to the desired
    ``Stanford Knees`` dataset version. Also the FFT needs to be centered. For example:

    .. code-block:: bash

        model:
            fft_centered: true
            fft_normalization: ortho

        train_ds:
            dataset_format: stanford_knees
            fft_centered: true
            fft_normalization: ortho

        validation_ds:
            dataset_format: stanford_knees
            fft_centered: true
            fft_normalization: ortho

        test_ds:
            dataset_format: stanford_knees
            fft_centered: true
            fft_normalization: ortho

For training a model, you just need to set up the data and export paths to the
`configuration <https://github.com/wdika/atommic/tree/main/projects/REC/StanfordKnees2019/conf/train/>`_
file of the model you want to train. In ``train_ds`` and `validation_ds` please set the ``data_path`` to the generated
json files. In ``exp_manager`` please set the ``exp_dir`` to the path where you want to save the model checkpoints and
tensorboard or wandb logs.

You can train a model with the following command:

.. code-block:: bash

    atommic run -c /projects/REC/StanfordKnees2019/conf/train/{model}.yaml

For testing a model, you just need to set up the data and export paths to the
`configuration <https://github.com/wdika/atommic/tree/main/projects/REC/StanfordKnees2019/conf/test/>`_ file
model you want to test. In ``checkpoint`` (line 2) set the path the trained model checkpoint and in ``test_ds`` please
set the ``data_path``. In ``exp_manager`` please set the ``exp_dir`` to the path where the predictions and logs will
be saved.

You can test a model with the following command:

.. code-block:: bash

    atommic run -c /projects/REC/StanfordKnees2019/conf/test/{model}.yaml

**Note:** The default logger is tensorboard.