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Paper Abstract and Keywords
Presentation 2020-02-27 16:35
A Study on Region Segmentation of Color Laparoscopic Images after Contrast Enhancement Including Super-Resolution CNN by Image Regions
Norifumi Kawabata (Tokyo Univ. of Science), Toshiya Nakaguchi (Chiba Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) As one of image pre-processing method to detect, recognize, and estimate lesion or characteristic region in medical image processing, there are many studies improved performance and precision of processing by contrast enhancement or super-resolution. However, it is not clarified how condition is better to apply these methods. Therefore, we experimented and discussed on affect for color laparoscopic image quality by the difference of contrast enhancement method. As a result, we obtained knowledge of high similarity among patterns of adaptive histogram equalization in three methods. However, under these conditions, in the case of considering the region segmentation, it is not clarified how processing precision is better. In this paper, first we processed the contrast enhancement for the color laparoscopic frame image cut from surgery video under laparoscopy. Next, we processed super-resolution for generated image, and finally, we compared and discussed by PSNR, SSIM, and texture features for contrast.
Keyword (in Japanese) (See Japanese page) 
(in English) Laparoscopic Image / Image Region / Super-Resolution Convolutional Neural Network (SRCNN) / Contrast Enhancement / Texture Features / Region Segmentation / /  
Reference Info. ITE Tech. Rep., vol. 44, no. 6, ME2020-50, pp. 113-118, Feb. 2020.
Paper # ME2020-50 
Date of Issue 2020-02-20 (MMS, HI, ME, AIT) 
ISSN Print edition: ISSN 1342-6893    Online edition: ISSN 2424-1970
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Conference Information
Conference Date 2020-02-27 - 2020-02-28 
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 ME 
Conference Code 2020-02-HI-IE-ITS-MMS-ME-AIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Region Segmentation of Color Laparoscopic Images after Contrast Enhancement Including Super-Resolution CNN by Image Regions 
Sub Title (in English)  
Keyword(1) Laparoscopic Image  
Keyword(2) Image Region  
Keyword(3) Super-Resolution Convolutional Neural Network (SRCNN)  
Keyword(4) Contrast Enhancement  
Keyword(5) Texture Features  
Keyword(6) Region Segmentation  
1st Author's Name Norifumi Kawabata  
1st Author's Affiliation Tokyo University of Science (Tokyo Univ. of Science)
2nd Author's Name Toshiya Nakaguchi  
2nd Author's Affiliation Chiba University (Chiba Univ.)
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Speaker Author-1 
Date Time 2020-02-27 16:35:00 
Presentation Time 15 minutes 
Registration for ME 
Paper # MMS2020-22, HI2020-22, ME2020-50, AIT2020-22 
Volume (vol) vol.44 
Number (no) no.6 
Page pp.113-118 
Date of Issue 2020-02-20 (MMS, HI, ME, AIT) 

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