Fast fully automatic segmentation of the myocardium in 2D cine MR images

Authors:
Sandro Queirós;Daniel Barbosa;Brecht Heyde;Pedro Morais;Denis Friboulet;Piet Claus;Olivier Bernard;Jan D'hooge
Affiliations:
Cardiovascular Imaging and Dynamics, University of Leuven, Leuven, Belgium;Cardiovascular Imaging and Dynamics, University of Leuven, Leuven, Belgium,CREATIS, CNRS UMR5220, INSERM U630, Université de Lyon, France,INSA-LYON, Université Lyon 1, France;Cardiovascular Imaging and Dynamics, University of Leuven, Leuven, Belgium;Cardiovascular Imaging and Dynamics, University of Leuven, Leuven, Belgium;CREATIS, CNRS UMR5220, INSERM U630, Université de Lyon, France,INSA-LYON, Université Lyon 1, France;Cardiovascular Imaging and Dynamics, University of Leuven, Leuven, Belgium;CREATIS, CNRS UMR5220, INSERM U630, Université de Lyon, France,INSA-LYON, Université Lyon 1, France;Cardiovascular Imaging and Dynamics, University of Leuven, Leuven, Belgium
Venue:
FIMH'13 Proceedings of the 7th international conference on Functional Imaging and Modeling of the Heart
Year:
2013

Citing 3
Cited 0

Segmentation of Left Ventricle in Cardiac Cine MRI: An Automatic Image-Driven Method

FIMH '09 Proceedings of the 5th International Conference on Functional Imaging and Modeling of the Heart
Localizing Region-Based Active Contours

IEEE Transactions on Image Processing
B-Spline Explicit Active Surfaces: An Efficient Framework for Real-Time 3-D Region-Based Segmentation

IEEE Transactions on Image Processing

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Abstract

A novel automatic initialization procedure for left ventricle (LV) cardiac magnetic resonance (CMR) segmentation is proposed through the combination of a LV localization method based on multilevel Otsu thresholding and an elliptical annular template matching algorithm. We then propose to adapt the recent B-spline Explicit Active Surfaces (BEAS) framework to the properties of CMR images by integrating two dedicated energy terms: a weighted localized Chan-Vese region-based energy to explicitly control the equilibrium point between the two regions around each interface and a combined local and global region-based formulation for the myocardial region. The proposed method has been validated on 45 mid-ventricular images taken from the 2009 MICCAI LV segmentation challenge. Results show the efficiency of our method both in terms of shape accuracy and computational times.