Robust atlas-based segmentation of highly variable anatomy: left atrium segmentation
Author(s)Depa, Michal; Sabuncu, Mert R.; Holmvang, Godtfred; Nezafat, Reza; Schmidt, Ehud J.; Golland, Polina; ... Show more Show less
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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.
DepartmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Statistical atlases and computational models of the heart (Lecture notes in computer science, v. 6364)
Depa, Michal et al. “Robust Atlas-Based Segmentation of Highly Variable Anatomy: Left Atrium Segmentation.” Statistical Atlases and Computational Models of the Heart. (Lecture notes in computer science, v. 6364) Springer Berlin / Heidelberg, 2010. 85-94. Copyright © 2010, Springer
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