@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/
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
.pklfile contains a T1 weighted brain MRI and its corresponding subcortical segmentation. You can read.pklfile 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 Dataset from Google Drive (1.44G)
Demographic information
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.