Automatic extraction of a kidney contour by narrowing 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

We extract a kidney region 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 publicationProceedings of the SICE Annual Conference
Pages128-131
Number of pages4
Publication statusPublished - 2005
Externally publishedYes
EventSICE Annual Conference 2005 - Okayama, Japan
Duration: 2005 Aug 82005 Aug 10

Other

OtherSICE Annual Conference 2005
CountryJapan
CityOkayama
Period05/8/805/8/10

Fingerprint

Neural networks

Keywords

  • Automatic extraction
  • Kidney
  • NN
  • Q-learning
  • Snakes
  • X-ray CT Images

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Kubota, Y., Mitsukura, Y., Fukumi, M., Akamatsu, N., & Yasutomo, M. (2005). Automatic extraction of a kidney contour by narrowing region based on the Q-learning. In Proceedings of the SICE Annual Conference (pp. 128-131)

Automatic extraction of a kidney contour by narrowing region based on the Q-learning. / Kubota, Yoshiki; Mitsukura, Yasue; Fukumi, Minoru; Akamatsu, Norio; Yasutomo, Motokatsu.

Proceedings of the SICE Annual Conference. 2005. p. 128-131.

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

Kubota, Y, Mitsukura, Y, Fukumi, M, Akamatsu, N & Yasutomo, M 2005, Automatic extraction of a kidney contour by narrowing region based on the Q-learning. in Proceedings of the SICE Annual Conference. pp. 128-131, SICE Annual Conference 2005, Okayama, Japan, 05/8/8.
Kubota Y, Mitsukura Y, Fukumi M, Akamatsu N, Yasutomo M. Automatic extraction of a kidney contour by narrowing region based on the Q-learning. In Proceedings of the SICE Annual Conference. 2005. p. 128-131
Kubota, Yoshiki ; Mitsukura, Yasue ; Fukumi, Minoru ; Akamatsu, Norio ; Yasutomo, Motokatsu. / Automatic extraction of a kidney contour by narrowing region based on the Q-learning. Proceedings of the SICE Annual Conference. 2005. pp. 128-131
@inproceedings{f83e1b402e174d7e8837dafe32b9e7b9,
title = "Automatic extraction of a kidney contour by narrowing region based on the Q-learning",
abstract = "We extract a kidney region 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.",
keywords = "Automatic extraction, Kidney, NN, Q-learning, Snakes, X-ray CT Images",
author = "Yoshiki Kubota and Yasue Mitsukura and Minoru Fukumi and Norio Akamatsu and Motokatsu Yasutomo",
year = "2005",
language = "English",
pages = "128--131",
booktitle = "Proceedings of the SICE Annual Conference",

}

TY - GEN

T1 - Automatic extraction of a kidney contour by narrowing region based on the Q-learning

AU - Kubota, Yoshiki

AU - Mitsukura, Yasue

AU - Fukumi, Minoru

AU - Akamatsu, Norio

AU - Yasutomo, Motokatsu

PY - 2005

Y1 - 2005

N2 - We extract a kidney region 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.

AB - We extract a kidney region 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.

KW - Automatic extraction

KW - Kidney

KW - NN

KW - Q-learning

KW - Snakes

KW - X-ray CT Images

UR - http://www.scopus.com/inward/record.url?scp=33645300717&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33645300717&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:33645300717

SP - 128

EP - 131

BT - Proceedings of the SICE Annual Conference

ER -