| Presentation | 2018-11-06 Improvement of Laparoscopic Color Image Diagnosis for Automatic Detection of Coded Defect Region and Application of Effective Classifier Parameter Norifumi Kawabata, Toshiya Nakaguchi, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In addition to judgment by human eyes up to the present, it is advanced for R&D of diagnostic imaging systems by using artificial intelligence positively. Particularly, from informatics, medical engineering field, it is needed for the automatic diagnosis based on image processing to achieve laparoscopic surgery support. Compared to images in the engineering field, it is difficult in the medical images for quantitative judgment and assessment of the coded defect and degradation. Therefore, we also need to consider color information including human visual characteristics and the application of classifier parameter for image information. In this study, first we judged using PSNR whether we can detect the coded defect or not after processing of H.265/HEVC for the certain region in frame images cut from laparoscopic video acquired using endoscopy. Next, we analyzed color information using S-CIELAB color space. Finally, we applied classifier parameter effectively, and discussed for medical image diagnosis. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Peak Signal to Noise Ratio / S-CIELAB Color Space / CIEDE2000 / Support Vector Machine |
| Paper # | MICT2018-42,MI2018-42 |
| Date of Issue | 2018-10-30 (MICT, MI) |
| Conference Information | |
| Committee | MICT / MI |
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| Conference Date | 2018/11/6(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | University of Hyogo |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Shinsuke Hara(Osaka City Univ.) / Kensaku Mori(Nagoya Univ.) |
| Vice Chair | Chika Sugimoto(Yokohama National Univ.) / Eisuke Hanada(Saga Univ.) / Yoshiki Kawata(Tokushima Univ.) / Yuichi Kimura(Kinki Univ.) |
| Secretary | Chika Sugimoto(Nagoya Inst. of Tech.) / Eisuke Hanada(Meiji Univ.) / Yoshiki Kawata(Aichi Inst. of Tech.) / Yuichi Kimura(Nagoya Inst. of Tech.) |
| Assistant | Takumi Kobayashi(Yokohama National Univ.) / Shintaro Izumi(Kobe Univ.) / Ami Tanaka(Ritsumeikan Univ.) / Keita Saku(Kyushu Univ.) / Ryo Haraguchi(Univ. of Hyogo) / Yasushi Hirano(Yamaguchi Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Healthcare and Medical Information Communication Technology / Technical Committee on Medical Imaging |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Improvement of Laparoscopic Color Image Diagnosis for Automatic Detection of Coded Defect Region and Application of Effective Classifier Parameter |
| Sub Title (in English) | |
| Keyword(1) | Peak Signal to Noise Ratio |
| Keyword(2) | S-CIELAB Color Space |
| Keyword(3) | CIEDE2000 |
| Keyword(4) | Support Vector Machine |
| 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.) |
| Date | 2018-11-06 |
| Paper # | MICT2018-42,MI2018-42 |
| Volume (vol) | vol.118 |
| Number (no) | MICT-285,MI-286 |
| Page | pp.pp.21-26(MICT), pp.21-26(MI), |
| #Pages | 6 |
| Date of Issue | 2018-10-30 (MICT, MI) |