Robust atlas-based segmentation of highly variable anatomy: left atrium segmentation
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Golland_Robust atlas.pdf
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2.49 MB
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Author(s)
Depa, Michal
Sabuncu, Mert R.
Holmvang, Godtfred
Nezafat, Reza
Schmidt, Ehud J.
Golland, Polina
Date Issued
January 2010
Journal
Statistical atlases and computational models of the heart (Lecture notes in computer science, v. 6364)
Publisher
Springer
Citation
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
Version
Author's final manuscript
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
https://doi.org/10.1007/978-3-642-15835-3_9
