Author(s)

Masahiro Ishikawa, Sercan Taha Ahi, Fumikazu Kimura, Masahiro Yamaguchi, Hiroshi Nagahashi, Akinori Hashiguchi, Michiie Sakamoto

Department of Pathology, Graduate School of Medicine, Keio University, Shinjuku-ku, Japan.
Global Scientific Information and Computing Center, Tokyo Institute of Technology, Meguroku, Japan.
Global Scientific Information and Computing Center, Tokyo Institute of Technology, Meguroku, Japan; Faculty of Health & Medical Care, Saitama Medical University, Hidaka-shi, Japan.

The liver comprises cell layers of hepatocytes called trabeculae, which are separated by vascular sinusoids. Under- standing the structure of hepatic trabeculae and liver sinusoids in hematoxylin and eosin (HE)-stained liver specimens is important for the differential diagnosis of liver diseases. In this study, we develop an approach to extracting liver sinusoids from HE-stained images. The proposed approach involves: 1) a new orientation-selective filter (OS filter) for edge enhancement and image denoising, 2) the clustering of image pixels to identify candidate sinusoids, and 3) a classification procedure that discards unlikely candidates and selects the final sinusoid areas. Experimental studies using a database of 16 images with a resolution of 512 × 512 pixels showed that the proposed approach could segment liver sinusoid pixels with 81% of specificity and 94% of sensitivity. A comparison with a method based on bilateral filters showed that this method improved the sensitivity for all images with an average improvement of 4% and no difference in specificity. The results were presented to a group of pathologists and they confirmed that the images were highly representative of the tissue morphology features.

Histopathological Tissue Images; Orientation-Selective Filter; Segmentation of Sinusoids

M. Ishikawa, S. Taha Ahi, F. Kimura, M. Yamaguchi, H. Nagahashi, A. Hashiguchi and M. Sakamoto, "Segmentation of Sinusoids in Hematoxylin and Eosin Stained Liver Specimens Using an Orientation-Selective Filter," Open Journal of Medical Imaging, Vol. 3 No. 4, 2013, pp. 144-155. doi: 10.4236/ojmi.2013.34022.