Accurate computing, modeling and analysis of the whole heart substructures is important in the development of clinical applications. Segmentation and registration of whole heart images is however challenging and still relies heavily on manual work, which is time-consuming and prone to errors.
The Challenge provides 120 multi-modality cardiac images acquired in real clinical environment. It aims at creating an open and fair competition for various research groups to test and validate their methods, particularly for the multi-modality whole heart segmentation. It is not only to benchmark various whole heart segmentation algorithms, but also to cover the topic of general cardiac image segmentation and registration and modeling.
For evaluation of the test data, the participants should prepare a brief description of their algorithm and email with the segmentation results of the test datasets to the organizers. The email should be titled MM-WHS Test Result + Fully Name of the corresponding author, and the segmentation results should be in nifty format in a zip file. All the results should have exactly the same image information as the original CT/MR images (including spacing, size, orientation info and short int data type etc), and the file names should be ct_test_20??_label.nii.gz (?? is the two digital index) or mr_test_20??_label.nii.gz. A method can only be evaluated once.
 Xiahai Zhuang and Juan Shen: Multi-scale patch and multi-modality atlases for whole heart segmentation of MRI, Medical Image Analysis, vol.31, pp.77-87, 2016 (download)
 Xiahai Zhuang: Challenges and Methodologies of Fully Automatic Whole Heart Segmentation: A Review. Journal of Healthcare Engineering 4 (3): 371–407, 2013 (download)
 Zhuang, X., Rhode, K., Razavi, R., Hawkes, D. J., Ourselin, S.: A Registration-Based Propagation Framework for Automatic Whole Heart Segmentation of Cardiac MRI. IEEE Transactions on Medical Imaging, 29 (9): 1612-1625, 2010. (download)