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

Authors:
Yoshiki Kubota;Yasue Mitsukura;Minoru Fukumi;Norio Akamatsu;Motokatsu Yasutomo
Affiliations:
The University of Tokushima, Tokushima, Japan;Okayama University, Okayama, Japan;The University of Tokushima, Tokushima, Japan;The University of Tokushima, Tokushima, Japan;Higashi Tokushima National Hospital, Tokushima, Japan
Venue:
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Year:
2005

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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.