A fuzzy logic rule-based system for chromosome recognition

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. We describe how fuzzy logic is being inserted into a complete karyotyping system to deal with uncertainty in similar chromosome classes