Classification of sarcomas using textural features

T. Tanaka, Y. Murase

Research output: Contribution to journalConference article

2 Citations (Scopus)

Abstract

This paper deals with classification of sarcomas using textural features. We assume that sarcomas have single texture and the same scale is used for photographing sarcoma's images. 80 sorts of sarcomas are selected under those assumptions. First, we make database of templates of sarcomas using textural features. The intensity histogram, Fourier power spectrum, run-length matrix, fractal dimension and co-occurrence matrix are used as textural features. Second, sarcomas are collated by using template matching between unknown samples and the templates in the database. The success rate reached 92%. The result of this experiment shows the adequateness of proposed system.

Original languageEnglish
Pages (from-to)682-685
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume1
Publication statusPublished - 2000 Dec 1
Event22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Chicago, IL, United States
Duration: 2000 Jul 232000 Jul 28

ASJC Scopus subject areas

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

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