| 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 |
| Download PDF |
|
| Conference Information |
| Committee |
HI IEICE-IE IEICE-ITS MMS ME AIT |
| 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 |
| Keyword(7) |
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| Keyword(8) |
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| 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 |
| #Pages |
6 |
| Date of Issue |
2020-02-20 (MMS, HI, ME, AIT) |
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