Presentation 2004/6/18
Automatic Extraction of a Kidney Region by Using the Q-learning
Yoshiki Kubota, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu, Motokatu Yasutomo,
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Abstract(in English) In these years, by aging population and Western-style food, kidney disease patients are increasing. It is difficult for people to recover all of kidney disease, early detection of a kidney disease is needed. But diagnosis of CT images has a fault that is time-consuming and a great labor is required since the quantity of CT images is huge. In this study, we propose a method that automatically extracts a kidney domain as a preprocessing of kidney failure detection. The kidney region is detected by contour information that is extracted from the CT image, by using the dynamic gray scale value refinement method by Q-learning. By using the proposed method, it is possible to detect stably the kidney from any patients.
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Keyword(in English) X-ray CT Images / kidney / automatically / dynamic gray scale value refinement / Q-learning
Paper # NC2004-38
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Committee NC
Conference Date 2004/6/18(1days)
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Paper Information
Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Automatic Extraction of a Kidney Region by Using the Q-learning
Sub Title (in English)
Keyword(1) X-ray CT Images
Keyword(2) kidney
Keyword(3) automatically
Keyword(4) dynamic gray scale value refinement
Keyword(5) Q-learning
1st Author's Name Yoshiki Kubota
1st Author's Affiliation Faculty of Engineering, Tokushima University()
2nd Author's Name Yasue Mitsukura
2nd Author's Affiliation Kyoiku, Okayama University
3rd Author's Name Minoru Fukumi
3rd Author's Affiliation Faculty of Engineering, Tokushima University
4th Author's Name Norio Akamatsu
4th Author's Affiliation Faculty of Engineering, Tokushima University /
5th Author's Name Motokatu Yasutomo
5th Author's Affiliation
Date 2004/6/18
Paper # NC2004-38
Volume (vol) vol.104
Number (no) 140
Page pp.pp.-
#Pages 5
Date of Issue