Paper Abstract and Keywords |
Presentation |
2016-03-03 09:50
A Type Identification System Based on Support Vector Machine in Computer Aided Diagnosis for Colorectal Endoscopic Images Takumi Okamoto, Tetsushi Koide, Tatsuya Shimizu, Koki Sugi, Anh-Tuan Hoang, Hikaru Sato, Toru Tamaki, Bisser Raytchev, Kazufumi Kaneda (Hiroshima Univ.), Shigeto Yoshida, Hiroshi Mieno (Hiroshima General Hospital), Shinji Tanaka (Hiroshima Univ.) MW2015-188 ICD2015-111 Link to ES Tech. Rep. Archives: MW2015-188 ICD2015-111 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
This paper describes a type identification processing in our eCAD system for colorectal endoscopic Full HD images with Narrow Band Imaging (NBI) magnification findings. In order to make a clear presentation of an identified result of Full HD to clinical doctors by raster scanning, it is necessary to develop a computation method with hierarchical combination of multi Scan Window (SW) sizes. For these images that are easily miss-identified due to the local information, we suggest that they should be removed from the learning dataset as avoid the images. As a result the software simulation, verifies the increase identification performance, in which type A or type A ̅ identifier of SW size 60×60 pixel, in comparison with original learning dataset. We also confirm the increase type B or type C3 identifier with RBF kernel function. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Full HD Image Recognition / Computer-Aided Diagnosis (CAD) / Support Vector Machine (SVM) / Type identification / FPGA / / / |
Reference Info. |
IEICE Tech. Rep., vol. 115, no. 477, ICD2015-111, pp. 85-90, March 2016. |
Paper # |
ICD2015-111 |
Date of Issue |
2016-02-24 (MW, ICD) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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MW2015-188 ICD2015-111 Link to ES Tech. Rep. Archives: MW2015-188 ICD2015-111 |
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