TY - GEN
T1 - Automatic extraction system of a kidney region based on the Q-learning
AU - Kubota, Yoshiki
AU - Mitsukura, Yasue
AU - Fukumi, Minoru
AU - Akamatsu, Norio
AU - Yasutomo, Motokatsu
PY - 2005/12/1
Y1 - 2005/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=33745291744&partnerID=8YFLogxK
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M3 - Conference contribution
AN - SCOPUS:33745291744
SN - 3540288945
SN - 9783540288947
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1261
EP - 1267
BT - Knowledge-Based Intelligent Information and Engineering Systems - 9th International Conference, KES 2005, Proceedings
T2 - 9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005
Y2 - 14 September 2005 through 16 September 2005
ER -