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Proceedings Paper

An algorithm to evaluate the number of trabecular cell layers using nucleus arrangement applied to hepatocellular carcinoma
Author(s): Hideki Komagata; Naoki Kobayashi; Ayako Katoh; Yasuka Ohnuki; Masahiro Ishikawa; Kazuma Shinoda; Masahiro Yamaguchi; Tokiya Abe; Akinori Hashiguchi; Michiie Sakamoto
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Paper Abstract

Recent advances in information technology have improved pathological virtual-slide technology and diagnostic support system studies of pathological images. Diagnostic support systems utilize quantitative indices determined by image processing. In previous studies on diagnostic support systems, carcinomatous areas of breast or lung have been recognized by the feature quantities of nuclear sizes, complexities, and internuclear distances based on graph theory, among other features. Improving recognition accuracy is important for the addition of new feature quantities. We focused on hepatocellular carcinoma (HCC) and investigated new feature quantities of histological images of HCC. One of the most important histological features of HCC is the trabecular pattern. For diagnosing cancer, it is important to recognize the tumor cell trabeculae. We propose a new algorithm for calculating the number of cell layers in histological images of HCC in tissue sections stained by hematoxylin and eosin. For the calculation, we used a Delaunay diagram that was based on the median points of nuclei, deleted the sinusoid and fat droplet regions from the Delaunay diagram, and counted the Delaunay lines while applying a thinning algorithm. Moreover, we experimented with the calculation of the number of cell layers with our method for different histological grades of HCC. The number of cell layers discriminated tumor differentiations and Edmondson grades; therefore, our algorithm may serve as an index of HCC for diagnostic support systems.

Paper Details

Date Published: 29 March 2013
PDF: 8 pages
Proc. SPIE 8676, Medical Imaging 2013: Digital Pathology, 86760M (29 March 2013); doi: 10.1117/12.2006319
Show Author Affiliations
Hideki Komagata, Saitama Medical Univ. (Japan)
Naoki Kobayashi, Saitama Medical Univ. (Japan)
Ayako Katoh, Saitama Medical Univ. (Japan)
Yasuka Ohnuki, Saitama Medical Univ. (Japan)
Masahiro Ishikawa, Tokyo Institute of Technology (Japan)
Kazuma Shinoda, Saitama Medical Univ. (Japan)
Masahiro Yamaguchi, Tokyo Institute of Technology (Japan)
Tokiya Abe, Keio Univ. (Japan)
Akinori Hashiguchi, Keio Univ. (Japan)
Michiie Sakamoto, Keio Univ. (Japan)

Published in SPIE Proceedings Vol. 8676:
Medical Imaging 2013: Digital Pathology
Metin N. Gurcan; Anant Madabhushi, Editor(s)

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