Fuzzy logic rule-based system for chromosome recognition

James M. Keller, Paul Gader, Ozy Sjahputera, C. William Caldwell, Hui Ming Tim Huang

Research output: Contribution to journalConference articlepeer-review

12 Scopus citations


One of the longest standing problems in medical image analysis is that of the automated recognition of chromosomes from images of a metaphase spread of a cell. This process of visualizing and categorizing the chromosomes within a cell, called karyotyping, is a key factor in many medical procedures. It is a labor intensive activity, and hence, is a great candidate for automation. However, there are many sources of uncertainty in this problem domain, making complete karyotyping a difficult problem. In this paper, we describe how fuzzy logic is being inserted into a complete karyotyping system to deal with uncertainty in similar chromosome classes.

Original languageEnglish (US)
Pages (from-to)125-132
Number of pages8
JournalProceedings of the IEEE Symposium on Computer-Based Medical Systems
StatePublished - Jan 1 1995
Externally publishedYes
EventProceedings of the 8th IEEE Symposium on Computer-Based Medical Systems - Lubbock, TX, USA
Duration: Jun 9 1995Jun 10 1995

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications


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