Abstract
In this paper, a kidney region is extracted as a preprocessing of kidney disease detection. The kidney region is detected based on its contour information that is extracted from a CT image using a dynamic gray scale value refinement method based on the Q-learning. An initial point to extract the kidney contour is decided by training gray scale values along horizontal direction with Neural Network (NN). Furthermore the kidney contour is corrected by using the snakes more accurately. It is demonstrated that the proposed method can detect stably the kidney contour from CT images of any patients.
| Original language | English |
|---|---|
| Title of host publication | Knowledge-Based Intelligent Information and Engineering Systems - 9th International Conference, KES 2005, Proceedings |
| Pages | 1261-1267 |
| Number of pages | 7 |
| Publication status | Published - 2005 Dec 1 |
| Externally published | Yes |
| Event | 9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005 - Melbourne, Australia Duration: 2005 Sep 14 → 2005 Sep 16 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 3681 LNAI |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005 |
|---|---|
| Country | Australia |
| City | Melbourne |
| Period | 05/9/14 → 05/9/16 |
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
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Cite this
Kubota, Y., Mitsukura, Y., Fukumi, M., Akamatsu, N., & Yasutomo, M. (2005). Automatic extraction system of a kidney region based on the Q-learning. In Knowledge-Based Intelligent Information and Engineering Systems - 9th International Conference, KES 2005, Proceedings (pp. 1261-1267). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3681 LNAI).