| Paper Abstract and Keywords |
| Presentation |
2020-11-04 15:50
[Short Paper]
An Experimental Study on Color Laparoscopic High-Definition Video Quality Assessment Including Super-resolution Norifumi Kawabata (Tokyo Univ. of Science), Toshiya Nakaguchi (Chiba Univ.) MICT2020-19 MI2020-45 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
After considering medical image analysis support, it is one of importance factors to assess high-definition image quality for high-definition display. In case of processing recognition and detection of body region and lesion in medical images, it is not enough to judge the only information of still image or some frame images. To find out image content and characteristics more accurately, we need to consider image quality from information obtained by video. In this paper, in the case of changing bit rate and focusing on image quality for color laparoscopic high-definition video including super-resolution, we carried out the objective assessment experiment by using PSNR, SSIM among frame of image, bit rate of video. Finally, we discussed with regard to display of medical image. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Laparoscopic Video / Super-Resolution Convolutional Neural Network (SRCNN) / Bit Rate / H.265/HEVC / Video Quality Assessment / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 120, no. 220, MI2020-45, pp. 60-61, Nov. 2020. |
| Paper # |
MI2020-45 |
| Date of Issue |
2020-10-28 (MICT, MI) |
| ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
| Download PDF |
MICT2020-19 MI2020-45 |
| Conference Information |
| Committee |
MICT MI |
| Conference Date |
2020-11-04 - 2020-11-04 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Online |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
Medical imaging technology, healthcare and medical information communication technology |
| Paper Information |
| Registration To |
MI |
| Conference Code |
2020-11-MICT-MI |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
An Experimental Study on Color Laparoscopic High-Definition Video Quality Assessment Including Super-resolution |
| Sub Title (in English) |
|
| Keyword(1) |
Laparoscopic Video |
| Keyword(2) |
Super-Resolution Convolutional Neural Network (SRCNN) |
| Keyword(3) |
Bit Rate |
| Keyword(4) |
H.265/HEVC |
| Keyword(5) |
Video Quality Assessment |
| Keyword(6) |
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| 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 |
2020-11-04 15:50:00 |
| Presentation Time |
20 minutes |
| Registration for |
MI |
| Paper # |
MICT2020-19, MI2020-45 |
| Volume (vol) |
vol.120 |
| Number (no) |
no.219(MICT), no.220(MI) |
| Page |
pp.60-61 |
| #Pages |
2 |
| Date of Issue |
2020-10-28 (MICT, MI) |