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Oda, H.* ; Roth, H.R.* ; Bhatia, K.K.* ; Oda, M.* ; Kitasaka, T.* ; Akita, T.* ; Schnabel, J.A.* ; Mori, K.*

TBS: Tensor-based supervoxels for unfolding the heart.

In: (International Conference on Medical Image Computing and Computer-Assisted Intervention). Berlin [u.a.]: Springer, 2017. 681-689 (Lect. Notes Comput. Sc. ; 10433 LNCS)
DOI
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Investigation of the myofiber structure of the heart is desired for studies of anatomy and diseases. However, it is difficult to understand the left ventricle structure intuitively because it consists of three layers with different myofiber orientations. In this work, we propose an unfolding method for micro-focus X-ray CT (µCT) volumes of the heart. First, we explore a novel supervoxel over-segmentation technique, Tensor-Based Supervoxels (TBS), which allows us to divide the left ventricle into three layers. We utilize TBS and B-spline curves for extraction of the layers. Finally we project µCT intensities in each layer to an unfolded view. Experiments are performed using three µCT images of the left ventricle acquired from canine heart specimens. In all cases, the myofiber structure could be observed clearly in the unfolded views. This is promising for helping cardiac studies.
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Publikationstyp Artikel: Konferenzbeitrag
Korrespondenzautor
Schlagwörter 3d Deformation ; Cardiac Anatomy ; Iterative Clustering
ISSN (print) / ISBN 0302-9743
e-ISSN 1611-3349
Konferenztitel International Conference on Medical Image Computing and Computer-Assisted Intervention
Zeitschrift Lecture Notes in Computer Science
Quellenangaben Band: 10433 LNCS, Heft: , Seiten: 681-689 Artikelnummer: , Supplement: ,
Verlag Springer
Verlagsort Berlin [u.a.]
Nichtpatentliteratur Publikationen
Institut(e) Institute for Machine Learning in Biomed Imaging (IML)