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Erschienen in:
2010 | OriginalPaper | Buchkapitel
Robust Atlas-Based Segmentation of Highly Variable Anatomy: Left Atrium Segmentation
verfasst von : Michal Depa, Mert R. Sabuncu, Godtfred Holmvang, Reza Nezafat, Ehud J. Schmidt, Polina Golland
Erschienen in: Statistical Atlases and Computational Models of the Heart
Verlag: Springer Berlin Heidelberg
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Automatic segmentation of the heart’s left atrium offers great benefits for planning and outcome evaluation of atrial ablation procedures. However, the high anatomical variability of the left atrium presents significant challenges for atlas-guided segmentation. In this paper, we demonstrate an automatic method for left atrium segmentation using weighted voting label fusion and a variant of the demons registration algorithm adapted to handle images with different intensity distributions. We achieve accurate automatic segmentation that is robust to the high anatomical variations in the shape of the left atrium in a clinical dataset of MRA images.