CDEMRIS fibrosis scar challenge dataset
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dataset
posted on 2016-11-09, 10:43 authored by Rashed KarimRashed KarimThe Dataset
This can be important for treatment stratification of patients with atrial fibrillation (AF) and for assessment of treatment after radio frequency catheter ablation (RFCA).
The datasets included are from a segmentation challenge where the aim was to create a benchmarking framework for algorithms classifying fibrosis and scar from LGE CMR images.
Dataset contents
The dataset includes two subsets called pre and post. These refer to the time-points when the images were acquired. The pre data contains pre-ablation imaging of fibrosis. The 'post' data contains the post-ablation imaging data. There are 30 datasets in each pre and post folders.
The folders are arranged as pXX, where XX is the case number. Within each folder you will find two images in NRRD format.
These images follow a naming convention:
- de_xx_nn
- la_seg_xx_nn
- The 'xx' can be 'a' or 'b'. The 'a' refers to the pre-scan and the 'b' refers to the post-scan.
- The 'nn' refers to the case number
Note the de_xx_nn refers to the delayed-enhancement (DE) scan. And the la_seg_xx_nn refers to the binary segmentation of the left atrial endocardium. The segmentation is registered to the delayed-enhancement scan. The images will generally be of varying quality.
References
Karim et. al. Evaluation of current algorithms for segmentation of scar tissue from late Gadolinium enhancement cardiovascular magnetic resonance of the left atrium in Journal of Cardiovascular Magnetic Resonance, 15(105), 2013. Link
