Automatic diagnosis supporting system for cervical cancer using image processing

Ayaka Iwai, Toshiyuki Tanaka

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

7 Citations (Scopus)

Abstract

In this paper, we suggest methods of automated screening system for cervical cancer to support cyto-pathologists because there is the lack of number of pathologists. It is important to extract nuclei accurately for the automatic diagnosis supporting system. Cells firstly need to be divided into the blue cells and red ones because cells are dyed in different colors based on type of cell: superficial, intermediate squamous and basal cells. Nuclei are then extracted by superpixel segmentation. Finally, we detect malignant cells by nuclear enlargement and color density of nuclei, and distinguish between positive images and negative ones.

Original languageEnglish
Title of host publication2017 56th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages479-482
Number of pages4
Volume2017-November
ISBN (Electronic)9784907764579
DOIs
Publication statusPublished - 2017 Nov 10
Event56th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2017 - Kanazawa, Japan
Duration: 2017 Sept 192017 Sept 22

Other

Other56th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2017
Country/TerritoryJapan
CityKanazawa
Period17/9/1917/9/22

Keywords

  • Cervical cancer
  • Diagnosis supporting system
  • Image processing

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Optimization
  • Control and Systems Engineering
  • Instrumentation

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