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Brainweb-DL

Welcome to Brainweb-DL, a powerful Python toolkit for downloading and converting the Brainweb dataset.

Features

  • Effortless Dataset Management: Automatically download, cache, and format the Brainweb dataset with ease. Convert it to the convenient nifti format or numpy array hassle-free.

  • Multiple Image Generation: Generate high-quality T1, T2, T2*, and PD images directly from the Brainweb dataset. Perfect for testing purposes, although keep in mind that the values provided are approximate.

Available data

The Brainweb project kindly provides:

  • A normal brain phantom (named subject 0 afterwards), with T1, T2 and PD contrasts, with a variety of noise levels and intensity non-uniformities. As well as a anatomical model (in the form of either crisp or fuzzy segmentation of brain tissues, at a fixed resolution of 181x217x181 images).
  • The same for a multiple sclerosis brain phantom (named subject 1 afterwards).
  • A set of 20 normal brains (with ids equal to [4, 5, 6, 18, 20, 38, 41-54]) , with a T1 contrast (with 1mm resolution at (181, 217,181)), as well as the crisp and fuzzy segmentation of brain tissues (with a shape of (362, 434,362)) 1.

This project provides a CLI and a Python API to download and convert theses data. On top of that, it can generate new contrasts (e.g. T2*) from the segmentations, and reshape the data to the desired resolution 2.

Get Started

Data Location

The cached data directory follows this priority order:

  1. User-specific argument (brainweb_dir in most functions)
  2. BRAINWEB_DIR environment variable
  3. ~/.cache/brainweb folder

Python Script Usage

from brainweb_dl import get_mri 

# Get the phantom with id 44 with a T1 constrast 
data = get_mri(sub_id=44, contrast="T1") 
# Gt the 3rd phantomn with a fuzzy segmentation of its tissues. 
data = get_mri(sub_id="3", contrast="fuzzy") 

# Check the docstring for more information.

The Brainweb dataset is downloaded and cached by default in the ~/.cache/brainweb folder.

Command Line Interface

brainweb-dl 44 --contrast=T1

For more information, see brainweb-dl --help.

Installation

Get up and running quickly!

pip install brainweb-dl

Development

Join our community and contribute to Brainweb-DL!

git clone git@github.com/paquiteau/brainweb-dl 
cd brainweb-dl
pip install -e .[dev,test,doc]

TODO List

Help us improve and shape the future of Brainweb-DL:

  • Add unit tests.
  • Implement fuzzy search and multiple subjects download in parallel.
  • Develop an interface to generate T1, T2, T2*, and PD images.
  • Enhance the search for the location of the Brainweb dataset (User > Environment Variable > Default Location).
  • Introduce an interface to download as BIDS format.

Acknowledgement

We extend our gratitude to the following for their contributions:

  • Casper De Clercq for the preliminary work and original idea. Check out his great work if you are interested in PET imaging and registration functionalities.

  • BrainWeb for providing this valuable dataset to the community.

:star2: If you like this work, don't forget to star it and share it 🌟

  1. Note that the classification of tissue is not the same as for subject 0 and 1 ↩

  2. This requires scipy to be installed. ↩

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