Segmenting the Papillary Muscles and the Trabeculae from High Resolution Cardiac CT through Restoration of Topological Handles

Mingchen Gao¹, Chao Chen¹, Shaoting Zhang¹, Zhen Qian², Dimitris Metaxas¹, and Leon Axel³

¹CBIM Center, Rutgers University, Piscataway, NJ 08854, USA

²2 Piedmont Heart Institute, Atlanta, GA 30309, USA

³New York University, 660 First Avenue, New York, NY 10016, USA

Abstract. We introduce a novel algorithm for segmenting the high resolution CT images of the left ventricle (LV), particularly the papillary muscles and the trabeculae. High quality segmentations of these structures are necessary in order to better understand the anatomical function and geometrical properties of LV. These fine structures, however, are extremely challenging to capture due to their delicate and complex nature in both geometry and topology. Our algorithm computes the potential missing topological structures of a given initial segmentation. Using techniques from computational topology, e.g. persistent homology, our algorithm find topological handles which are likely to be the true signal. To further increase accuracy, these proposals are measured by the saliency and confidence from a trained classifier. Handles with high scores are restored in the final segmentation, leading to high quality segmentation results of the complex structures.

LNCS 7917, p. 184 ff.

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