A color-based approach for automated segmentation in tumor tissue classification

Yi Ying Wang, Shao Chien Chang, Li Wha Wu, Sen Tien Tsai, Yung Nien Sun

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

11 Citations (Scopus)

Abstract

This paper presents a new color-based approach for automated segmentation and classification of tumor tissues from microscopic images. The method comprises three stages: (1) color normalization to reduce the quality variation of tissue image within samples from individual subjects or from different subjects; (2) automatic sampling from tissue image to eliminate tedious and time-consuming steps; and (3) principal component analysis (PCA) to characterize color features in accordance with a standard set of training data. We evaluate the algorithm by comparing the performance of the proposed fully-automated method against semi-automated procedures. Experimental studies show consist agreement between the two methods. Thus, the proposed algorithm provides an effective tool for evaluating oral cancer images. It can also be applied to other microscopic images prepared with the same type of tissue staining.

Original languageEnglish
Title of host publication29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
Pages6576-6579
Number of pages4
DOIs
Publication statusPublished - 2007 Dec 1
Event29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07 - Lyon, France
Duration: 2007 Aug 232007 Aug 26

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
ISSN (Print)0589-1019

Other

Other29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
CountryFrance
CityLyon
Period07-08-2307-08-26

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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