Name
Abstract | ||
|---|---|---|
Automation of chromosome analysis has long been considered as a very difficult task. Efforts to computerize some or all of the procedures using various conventional pattern recognition techniques have had only limited success. In this paper the previous work in this domain is briefly reviewed, with a discussion of the limitations of the existing approaches. An attempt to apply AI techniques is introduced, and the organization of an expert image analysis system for chromosome classification is described, mainly at a conceptual level. Based on the proposed architecture, the low-level processes (segmentation, feature extraction) and the high-level processes (classifications or interpretations) can be carried out in a knowledge-guided fashion with a combinational use of image processing and pattern recognition knowledge, as well as expert chromosome classification knowledge embedded in a rule-based structure. A knowledge-based chromosome image analysis scheme is presented which adopts a hierarchical hypothesize-and-verify paradigm. Example rules are given to illustrate how they can be used in this scheme. |
Year | DOI | Venue |
|---|---|---|
1987 | 10.1016/0950-7051(87)90006-2 | Knowledge-Based Systems |
Keywords | Field | DocType |
chromosome analysis,pattern recognition,hypothesize-and-verify,knowledge-based system | Data mining,Architecture,Computer science,Segmentation,Expert system,Image processing,Knowledge-based systems,Feature extraction,Automation,Artificial intelligence,Machine learning | Journal |
Volume | Issue | ISSN |
1 | 1 | 0950-7051 |
Citations | PageRank | References |
5 | 1.22 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Q. Wu | 1 | 5 | 1.22 |
| P. Suetens | 2 | 234 | 58.52 |
| Oosterlinck, A. | 3 | 711 | 254.21 |