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Article Dans Une Revue Medical Image Analysis Année : 2014

Right Ventricle Segmentation From Cardiac MRI: A Collation Study

Maria A. Zuluaga
Ismail Ben Ayed
  • Fonction : Auteur

Résumé

Magnetic Resonance Imaging (MRI), a reference examination for cardiac morphology and function in humans, allows to image the cardiac right ventricle (RV) with high spatial resolution. The segmentation of the RV is a dicult task due to the variable shape of the RV and its ill-de fined borders in these images. The aim of this paper is to evaluate several RV segmentation algorithms on common data. More precisely, we report here the results of the Right Ventricle Segmentation Challenge (RVSC), concretized during the MICCAI'12 Conference with an on-site competition. Seven automated and semi-automated methods have been considered, along them three atlasbased methods, two prior based methods, and two prior-free, image-driven methods that make use of cardiac motion. The obtained contours were compared against a manual tracing by an expert cardiac radiologist, taken as a reference, using Dice metric and Hausdor distance. We herein describe the cardiac data composed of 48 patients, the evaluation protocol and the results. Best results show that an average 80% Dice accuracy and a 1 cm Hausdor distance can be expected from semi-automated algorithms for this challenging task on the datasets, and that an automated algorithm can reach similar performance, at the expense of a high computational burden. Data are now publicly available and the website remains open for new submissions (http://www.litislab.eu/rvsc/).
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Dates et versions

hal-01081337 , version 1 (07-11-2014)

Identifiants

Citer

Caroline Petitjean, Maria A. Zuluaga, Wenjia Bai, Jean-Nicolas Dacher, Damien Grosgeorge, et al.. Right Ventricle Segmentation From Cardiac MRI: A Collation Study. Medical Image Analysis, 2014, 19 (1), pp.43. ⟨10.1016/j.media.2014.10.004⟩. ⟨hal-01081337⟩
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