Automatic segmentation of hepatocellular structure from HE-stained liver tissue

Masahiro Ishikawa; Sercan Taha Ahi; Yuri Murakami; Fumikazu Kimura; Masahiro Yamaguchi; Tokiya Abe; Akinori Hashiguchi; Michiie Sakamoto

doi:10.1117/12.2006669

29 March 2013 Automatic segmentation of hepatocellular structure from HE-stained liver tissue

Masahiro Ishikawa, Sercan Taha Ahi, Yuri Murakami, Fumikazu Kimura, Masahiro Yamaguchi, Tokiya Abe, Akinori Hashiguchi, Michiie Sakamoto

Author Affiliations +

Proceedings Volume 8676, Medical Imaging 2013: Digital Pathology; 867611 (2013) https://doi.org/10.1117/12.2006669
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

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%.

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Masahiro Ishikawa, Sercan Taha Ahi, Yuri Murakami, Fumikazu Kimura, Masahiro Yamaguchi, Tokiya Abe, Akinori Hashiguchi, and Michiie Sakamoto "Automatic segmentation of hepatocellular structure from HE-stained liver tissue", Proc. SPIE 8676, Medical Imaging 2013: Digital Pathology, 867611 (29 March 2013); https://doi.org/10.1117/12.2006669

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