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.
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Kubota, Y., Mitsukura, Y., Fukumi, M., Akamatsu, N., Yasutomo, M. (2005). Automatic Extraction System of a Kidney Region Based on the Q-Learning. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552413_180
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DOI: https://doi.org/10.1007/11552413_180
Publisher Name: Springer, Berlin, Heidelberg
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