Automatic segmentation of pathological tissues in cardiac MRI

Khaoula Elagouni (1) , Cybèle Ciofolo-Veit (1) , Benoît Mory (1)

1 Medisys - MedisysResearch Lab

In the context of cardiac viability assessment, we propose a new fully automatic method to segment and quantify myocardial pathological tissues in Late Enhancement Cardiac Magnetic Resonance images. Our two main contributions are a generic image intensity analysis and an original variational segmentation method, the Fast Region Competition. The obtained results are robust to anatomical variability and partial volume effects and false positives are avoided. To validate our results, we use representations that are independent of myocardium shape and size and compute clinically relevant indicators. The proposed method was tested on 100 slices and compared to other classical segmentation approaches, showing the best agreement with semi-automatic expert delineations. (c) 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.

Mots clés: Segmentation; variational methods; late-enhancement; myocardium viability

Domaines: Imagerie médicale; Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Khaoula Elagouni, Cybèle Ciofolo-Veit, Benoît Mory. Automatic segmentation of pathological tissues in cardiac MRI. 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Apr 2010, Rotterdam, Netherlands. pp.472-475, ⟨10.1109/ISBI.2010.5490306⟩. ⟨hal-00508765⟩