Share Email Print

Proceedings Paper

Automatic segmentation of hepatocellular structure from HE-stained liver tissue
Author(s): Masahiro Ishikawa; Sercan Taha Ahi; Yuri Murakami; Fumikazu Kimura; Masahiro Yamaguchi; Tokiya Abe; Akinori Hashiguchi; Michiie Sakamoto
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

The analysis of hepatic tissue structure is required for quantitative assessment of liver histology. Especially, a cord-like structure of liver cells, called trabecura, has important information in the diagnosis of hepatocellular carcinoma (HCC). However, the extraction of trabeculae is thought to be difficult because liver cells take on various colors and appearances depending on tissue conditions. In this paper, we propose an approach to extract trabeculae from images of hematoxyline and eosin stained liver tissue slide by extracting the rest of trabeculae: sinusoids and stromal area. The sinusoids are simply extracted based on the color information, where the image is corrected by an orientation selective filtering before segmentaion. The stromal area mainly consists of fiber, and often includes lymphocytes densely. Therefore, in the proposed method, fiber region and lymphocytes are extracted separately, then, stromal region is determined based on the extracted results. The determination of stroma is performed based on superpixels, to obtain precise boundaries. Once the regions of sinusoids and stroma are obtained, trabeculae can be segmented as the remaining region. The proposed method was applied to 10 test images of normal and HCC liver tissues, and the results were evaluated based on the manual segmentation. As a result, we confirmed that both sensitivity and specificity of the extraction of trabeculae reach around 90%.

Paper Details

Date Published: 29 March 2013
PDF: 7 pages
Proc. SPIE 8676, Medical Imaging 2013: Digital Pathology, 867611 (29 March 2013); doi: 10.1117/12.2006669
Show Author Affiliations
Masahiro Ishikawa, Tokyo Institute of Technology (Japan)
Sercan Taha Ahi, Tokyo Institute of Technology (Japan)
Yuri Murakami, Tokyo Institute of Technology (Japan)
Fumikazu Kimura, Tokyo Institute of Technology (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)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?