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Preprocessed IXI brain MRI dataset with subcortical segmentation

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Preprocessed IXI Dataset

Creative Commons License

❗ Our preprocessed IXI dataset is made available under the Creative Commons Attribution-ShareAlike 3.0 Unported License. If you use this dataset, you should acknowledge the TransMorph paper:
@article{chen2021transmorph,
title={TransMorph: Transformer for unsupervised medical image registration},
author={Chen, Junyu and Frey, Eric C and He, Yufan and Segars, William P and Li, Ye and Du, Yong},
journal={Medical Image Analysis},
year={2022}
}

and acknowledge the source of the IXI data: https://brain-development.org/ixi-dataset/

About the Dataset

This repository contains a preprocessed IXI brain MRI dataset (https://brain-development.org/ixi-dataset/) used in TransMorph.

  • Preprocessing: The IXI dataset was preprocessed (e.g., skull stripping, affine alignment, and subcortical segmentation) by using FreeSurfer. The steps we used are listed here - Brain MRI preprocessing and subcortical segmentation using FreeSurfer
  • Train-Val-Test split: There are 576 brain MRI volumes in total. We split the dataset into a ratio of 7:1:2, where 403 for training (IXI_data/Train/), 58 for validation (IXI_data/Val/), and 115 for testing (IXI_data/Test/).
  • Atlas image: Additionally, there is one atlas MRI volume and its corresponding subcortical segmentation (IXI_data/altas.pkl). This atlas volume was obtained from CycleMorph.
  • File format: Each .pkl file contains a T1 weighted brain MRI and its corresponding subcortical segmentation. You can read .pkl file in python by doing:
    import pickle
    def pkload(fname):
        with open(fname, 'rb') as f:
            return pickle.load(f)
    
    image, label = pkload("subject_0.pkl")
    # image: a preprocessed T1-weighted brain MRI volume. Shape: 160 x 192 x 224 Intensity: [0,1]
    # label: the corresponding subcortical segmentations. Shape: 160 x 192 x 224 Intensity: Integers
  • Label map: A description of each label and the corresponding indexing value is provided here.
  • Image size: Each image and label map has a size of 160 x 192 x 224.
  • Normalization: The intensity values of each image volume are normalized into a range [0,1].
  • Dataset structure:
    IXI_data/Train/------
            subject_0.pkl   <--- a brain T1 MR image and its label map
            subject_4.pkl
            .......
    IXI_data/Val/------
            subject_2.pkl
            subject_5.pkl
            .......
    IXI_data/Test/------
            subject_1.pkl
            subject_3.pkl
            .......
    IXI_data/atlas.pkl      <--- Atlas image and its label map

Download

Download Dataset from Google Drive (1.44G)
Demographic information

Atals-to-Patient Registration

Please visit https://github.com/junyuchen245/TransMorph_Transformer_for_Medical_Image_Registration/blob/main/TransMorph_on_IXI.md for instructions on network training, inference, and evaluation for medical image registration using this dataset.

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