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Paper Abstract and Keywords
Presentation 2019-02-19 16:30
A Fundamental Study on Laparoscopic Image Region Segmentation Based on Texture Analysis by Regions
Norifumi Kawabata (Nagoya Univ.), Toshiya Nakaguchi (Chiba Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) Most of image region segmentation studies can be divided to both subjective method by assessors and objective method by computers. Particularly, in medical images, since there are body region and border that it is hard for medical worker to distinguish by the only image diagnosis, we estimate that the progress of work, time, and emergency are needed. Therefore, it is problem of emergency to develop the medical information system enable to support medical workers by using high performance computer system. In previous, there were studies on the image processing method based on texture analysis of medical images. However, it is not clarified for region segmentation by body region how to apply. In this study, first, we carried out the texture analysis for region image of laparoscopic image. Next, based on analysis results, we experimented whether region segmentation of laparoscopic image is possible or impossible, and finally, we discussed how each texture features are affected to region segmentation.
Keyword (in Japanese) (See Japanese page) 
(in English) Laparoscopic Image / Texture Features / Gray-Level Co-Occurrence Matrix (GLCM) / Region Segmentation / Medical Image Diagnosis / / /  
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Conference Information
Committee ITS IE ITE-MMS ITE-HI ITE-ME ITE-AIT  
Conference Date 2019-02-19 - 2019-02-20 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image Processing, etc. 
Paper Information
Registration To ITE-ME 
Conference Code 2019-02-ME-IE-ITS-MMS-HI-AIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Fundamental Study on Laparoscopic Image Region Segmentation Based on Texture Analysis by Regions 
Sub Title (in English)  
Keyword(1) Laparoscopic Image  
Keyword(2) Texture Features  
Keyword(3) Gray-Level Co-Occurrence Matrix (GLCM)  
Keyword(4) Region Segmentation  
Keyword(5) Medical Image Diagnosis  
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1st Author's Name Norifumi Kawabata  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Toshiya Nakaguchi  
2nd Author's Affiliation Chiba University (Chiba Univ.)
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Speaker Author-1 
Date Time 2019-02-19 16:30:00 
Presentation Time 15 minutes 
Registration for ITE-ME 
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Volume (vol) vol.118 
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