Automatic quantification of morphological features for hepatic trabeculae analysis in stained liver specimens

Masahiro Ishikawa, Yuri Murakami, Sercan Taha Ahi, Masahiro Yamaguchi, Naoki Kobayashi, Tomoharu Kiyuna, Yoshiko Yamashita, Akira Saito, Tokiya Abe, Akinori Hashiguchi, Michiie Sakamoto

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

This paper proposes a digital image analysis method to support quantitative pathology by automatically segmenting the hepatocyte structure and quantifying its morphological features. To structurally analyze histopathological hepatic images, we isolate the trabeculae by extracting the sinusoids, fat droplets, and stromata. We then measure the morphological features of the extracted trabeculae, divide the image into cords, and calculate the feature values of the local cords. We propose a method of calculating the nuclear-cytoplasmic ratio, nuclear density, and number of layers using the local cords. Furthermore, we evaluate the effectiveness of the proposed method using surgical specimens. The proposed method was found to be an effective method for the quantification of the Edmondson grade.

Original languageEnglish
Article number027502
JournalJournal of Medical Imaging
Volume3
Issue number2
DOIs
Publication statusPublished - 2016 Apr 1

Keywords

  • hematoxylin and eosin-stained specimens
  • hepatic trabecula
  • quantitative pathology
  • segmentation

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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