Abstract
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 language | English (US) |
|---|---|
| Pages (from-to) | 125-132 |
| Number of pages | 8 |
| Journal | Proceedings of the IEEE Symposium on Computer-Based Medical Systems |
| State | Published - 1995 |
| Externally published | Yes |
| Event | Proceedings of the 8th IEEE Symposium on Computer-Based Medical Systems - Lubbock, TX, USA Duration: Jun 9 1995 → Jun 10 1995 |
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging
- Computer Science Applications