Automatic extraction system of a kidney region based on the Q-learning

Yoshiki Kubota, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu, Motokatsu Yasutomo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems - 9th International Conference, KES 2005, Proceedings
Pages1261-1267
Number of pages7
Publication statusPublished - 2005 Dec 1
Event9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005 - Melbourne, Australia
Duration: 2005 Sep 142005 Sep 16

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3681 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005
CountryAustralia
CityMelbourne
Period05/9/1405/9/16

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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).