The dataset contains selected slices from multi-center, used in the following papers (a)-(c).

(a). X. Zhuang et al., “Evaluation of algorithms for multi-modality whole heart segmentation: An open-access grand challenge,” Med. Image Anal., vol. 58, pp. 101537–101550, Dec. 2019.

(b). X. Zhuang and J. Shen, “Multi-scale patch and multi-modality atlases for whole heart segmentation of MRI,” Med. Image Anal., vol. 31, pp. 77–87, Jul. 2016.

(c). M. Schaap et al., “Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms,” Med. Image Anal., vol. 13, no. 5, pp. 701–714, Oct. 2009.

It contains five zipped files of CT and MR images as described below for evaluation of LV and Myocardium segmentation: LV Label = 500, Myo Label = 205. (Other labels like RV and atrium can be ignored, or used for your own purpose.)

The file `CT_withGT.zip' contains 20 cases of CT, each case has 16 slices from the long-axis view around the center of left ventricular cavity. We provided their ground truth for LV and Myocardium.

The file `CT_woGT.zip' constains 32 cases of CT, each case has 16 slices from the long-axis view around the center of left ventricular cavity. They do not have the manual labeled ground truth. We use the automatic segmentation method, i.w., M3AS [1], to abtain their pseudo-lables. Noting that these pseudo-lables can not be used for testing or validation, as there exists error in them.

The file ` MR_withGT.zip' contains 20 cases of MR, each case has 16 slices from the long-axis view around the center of left ventricular cavity. We provided their ground truth for LV and Myocardium.

The file ` MR_woGT0/1.zip' contains 26 cases of MR, each case has 16 slices from the long-axis view around the center of left ventricular cavity. They do not have the manual labeled ground truth. We use the automatic segmentation method, i.w., M3AS , to abtain their pseudo-lables. Noting that these pseudo-lables can not be used for testing or validation, as there exists error in them.

If you found the repository useful, please cite our work as below:

@ARTICLE{9165963,

  author={F. {Wu} and X. {Zhuang}},

  journal={IEEE Transactions on Medical Imaging}, 

  title={CF Distance: A New Domain Discrepancy Metric and Application to Explicit Domain Adaptation for Cross-Modality Cardiac Image Segmentation}, 

  year={2020},

  volume={},

  number={},

  pages={1-1},}

and

@article{Zhuang2016Multi,
  title={Multi-scale patch and multi-modality atlases for whole heart segmentation of MRI.},
  author={Zhuang, Xiahai and Shen, Juan},
  journal={Medical Image Analysis},
  pages={77-87},
  year={2016},
}

or

F. Wu and X. Zhuang, "CF Distance: A New Domain Discrepancy Metric and Application to Explicit Domain Adaptation for Cross-Modality Cardiac Image Segmentation," in IEEE Transactions on Medical Imaging, doi: 10.1109/TMI.2020.3016144.

1. X. Zhuang and J. Shen, “Multi-scale patch and multi-modality atlases for whole heart segmentation of MRI,” Medical image analysis, vol. 31, pp. 77–87, 2016.