Computational cell classification methodology for hepatocellular carcinoma

Chamidu Atupelage, Hiroshi Nagahashi, Fumikazu Kimura, Masahiro Yamaguchi, Tokiya Abe, Akinori Hashiguchi, Michiie Sakamoto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Liver cancer is one of the frequent causes of death in the world. Hepatocellular carcinoma (HCC) is the most common histological type of primary liver cancer. HCC can be graded according to the malignancy of the tumors. Generally, a HCC grade is determined based on the characteristics of liver cell nuclei. This paper illustrates a methodology for classifying liver cell nuclei and grading HCC histological images quantitatively. The liver cell nuclei are classified in three consecutive tasks: nuclear segmentation, fibrous region detection, and nuclear classification. Each task utilizes the pixel-based textural features that are obtained through multifractal computation on digital images. First, the system segments every possible type of nuclei and excludes the nuclei within fibrous regions. Then, it classifies the rest of the nuclei to discriminate liver cell nuclei. For tumor grading, this method utilizes the following four categories of nuclear features: inner texture, geometry, spatial distribution, and surrounding texture. The proposed method was employed to classify a set of HCC histological images into five.

Original languageEnglish
Title of host publicationInternational Conference on Advances in ICT for Emerging Regions, ICTer 2013 - Conference Proceedings
PublisherIEEE Computer Society
Pages21-27
Number of pages7
DOIs
Publication statusPublished - 2013
Event2013 International Conference on Advances in ICT for Emerging Regions, ICTer 2 - Colombo, Sri Lanka
Duration: 2013 Dec 122013 Dec 13

Other

Other2013 International Conference on Advances in ICT for Emerging Regions, ICTer 2
CountrySri Lanka
CityColombo
Period13/12/1213/12/13

Fingerprint

Liver
Cells
Tumors
Textures
Spatial distribution
Methodology
Pixels
Geometry
Grading
Tumor
Cancer
Texture

Keywords

  • Cancer grading
  • Feature selection
  • HCC histological images
  • Multifractal computation
  • Multifractal measures
  • Segmentation
  • Textural feature descriptor

ASJC Scopus subject areas

  • Management of Technology and Innovation

Cite this

Atupelage, C., Nagahashi, H., Kimura, F., Yamaguchi, M., Abe, T., Hashiguchi, A., & Sakamoto, M. (2013). Computational cell classification methodology for hepatocellular carcinoma. In International Conference on Advances in ICT for Emerging Regions, ICTer 2013 - Conference Proceedings (pp. 21-27). [6761150] IEEE Computer Society. https://doi.org/10.1109/ICTer.2013.6761150

Computational cell classification methodology for hepatocellular carcinoma. / Atupelage, Chamidu; Nagahashi, Hiroshi; Kimura, Fumikazu; Yamaguchi, Masahiro; Abe, Tokiya; Hashiguchi, Akinori; Sakamoto, Michiie.

International Conference on Advances in ICT for Emerging Regions, ICTer 2013 - Conference Proceedings. IEEE Computer Society, 2013. p. 21-27 6761150.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Atupelage, C, Nagahashi, H, Kimura, F, Yamaguchi, M, Abe, T, Hashiguchi, A & Sakamoto, M 2013, Computational cell classification methodology for hepatocellular carcinoma. in International Conference on Advances in ICT for Emerging Regions, ICTer 2013 - Conference Proceedings., 6761150, IEEE Computer Society, pp. 21-27, 2013 International Conference on Advances in ICT for Emerging Regions, ICTer 2, Colombo, Sri Lanka, 13/12/12. https://doi.org/10.1109/ICTer.2013.6761150
Atupelage C, Nagahashi H, Kimura F, Yamaguchi M, Abe T, Hashiguchi A et al. Computational cell classification methodology for hepatocellular carcinoma. In International Conference on Advances in ICT for Emerging Regions, ICTer 2013 - Conference Proceedings. IEEE Computer Society. 2013. p. 21-27. 6761150 https://doi.org/10.1109/ICTer.2013.6761150
Atupelage, Chamidu ; Nagahashi, Hiroshi ; Kimura, Fumikazu ; Yamaguchi, Masahiro ; Abe, Tokiya ; Hashiguchi, Akinori ; Sakamoto, Michiie. / Computational cell classification methodology for hepatocellular carcinoma. International Conference on Advances in ICT for Emerging Regions, ICTer 2013 - Conference Proceedings. IEEE Computer Society, 2013. pp. 21-27
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