An accurate method of extracting fat droplets in liver images for quantitative evaluation

Masahiro Ishikawa, Naoki Kobayashi, Hideki Komagata, Kazuma Shinoda, Masahiro Yamaguchi, Tokiya Abe, Akinori Hashiguchi, Michiie Sakamoto

研究成果: Conference contribution

3 被引用数 (Scopus)


The steatosis in liver pathological tissue images is a promising indicator of nonalcoholic fatty liver disease (NAFLD) and the possible risk of hepatocellular carcinoma (HCC). The resulting values are also important for ensuring the automatic and accurate classification of HCC images, because the existence of many fat droplets is likely to create errors in quantifying the morphological features used in the process. In this study we propose a method that can automatically detect, and exclude regions with many fat droplets by using the feature values of colors, shapes and the arrangement of cell nuclei. We implement the method and confirm that it can accurately detect fat droplets and quantify the fat droplet ratio of actual images. This investigation also clarifies the effective characteristics that contribute to accurate detection.

ホスト出版物のタイトルMedical Imaging 2015
ホスト出版物のサブタイトルDigital Pathology
編集者Metin N. Gurcan, Anant Madabhushi
出版ステータスPublished - 2015 1 1
イベントMedical Imaging 2015: Digital Pathology - Orlando, United States
継続期間: 2015 2 252015 2 26


名前Progress in Biomedical Optics and Imaging - Proceedings of SPIE


OtherMedical Imaging 2015: Digital Pathology
CountryUnited States

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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