TBS: Tensor-based supervoxels for unfolding the heart - Oda, Hirohisa; Roth, Holger R.; Bhatia, Kanwal K.; Oda, Masahiro; Kitasaka, Takayuki; Akita, Toshiaki; Schnabel, Julia A.; Mori, Kensaku (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2017)
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.
CRIS-Team Scopus Importer:2023-03-08
Keywords: 3D deformation; Cardiac anatomy; Iterative clustering