Evaluation of right ventricular structure and function is of importance in the management of most cardiac disorders [1]. RV imaging has always been considered challenging, mainly because of the complex motion and anatomy of the RV. Indeed RV segmentation in MR images involves many problems such as dealing with the highly variable, crescent shape of the RV and its thin and ill-defined borders. In the literature, several segmentation methods have been proposed, relying in particular on statistical shape modeling and/or 3D approaches, in order to deal with the aforementioned issues [2]. Because many segmentation algorithms in cardiac MRI jointly segment both ventricles, the database contains images with both ventricles clearly visible. Whereas the left ventricle (LV) segmentation in cardiac MRI has given rise to two segmentation challenges (part of MICCAI’09 and MICCAI’11), RV segmentation algorithms have never been assessed on common data. The aim of this challenge is to gather researchers in this field to advance towards clinical applications. Our challenge was part of a workshop 3D Cardiovascular Imaging: a MICCAI segmentation challenge at the 15th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), which was held on October 1st, 2012 in Nice Sophia Antipolis, France. This workshop also includes a challenge on Coronary Artery Stenoses Detection and Quantification.
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[1] J. Caudron, J. Fares, V. Lefebvre, P.-H. Vivier, C. Petitjean and J.-N. Dacher, Cardiac MR Assessment of Right Ventricular Function in Acquired Heart Disease: Factors of Variability, Academic Radiology, Volume 19, Issue 8, pp. 991-1002, 2012
[2] C. Petitjean and J.-N. Dacher, A review of segmentation methods in short-axis cardiac MRI, MedIA, 15(169-184), 2011