| Presentation | 2020-01-30 Bleeding area segmentation from laparoscopic video based on U-Net for laparoscopic surgery support Shota Yamamoto, Yuichiro Hayashi, Shintaro Morimitsu, Takuya Ozawa, Takayuki Kitasaka, Masahiro Oda, Nobuyoshi Takeshita, Masaaki Ito, Kensaku Mori, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | This paper reports a bleeding region segmentation method in laparoscopic videos based on U-Net for laparoscopic surgery assistance. Researches on recognition of surgical process have been conducted by analyzing laparoscopic videos for assisting laparoscopic surgery. We have focused on bleeding areas during surgery and have segmented bleeding areas from laparoscopic videos using U-Net. Since our previous method processed frame by frame in the videos, time-series smoothness was lost in the results. In this paper, we construct U-Net which considers time series information. In the experiment, we segmented the bleeding area in laparoscopic surgery videos by the previous method and proposed method. The experimental results showed that the bleeding region was extracted with continuity between frames by using multiple consecutive frames as input. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Laparoscopic surgery / Surgical process analysis / Segmentation / Deep learning |
| Paper # | MI2019-115 |
| Date of Issue | 2020-01-22 (MI) |
| Conference Information | |
| Committee | MI |
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| Conference Date | 2020/1/29(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | OKINAWAKEN SEINENKAIKAN |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Medical Image Engineering, Analysis, Recognition, etc. |
| Chair | Yoshiki Kawata(Tokushima Univ.) |
| Vice Chair | Takayuki Kitasaka(Aichi Inst. of Tech.) / Hidekata Hontani(Nagoya Inst. of Tech.) |
| Secretary | Takayuki Kitasaka(Yamaguchi Univ.) / Hidekata Hontani(Univ. of Hyogo) |
| Assistant | Hotaka Takizawa(Tsukuba Univ.) / Yoshito Otake(NAIST) |
| Paper Information | |
| Registration To | 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) | Bleeding area segmentation from laparoscopic video based on U-Net for laparoscopic surgery support |
| Sub Title (in English) | |
| Keyword(1) | Laparoscopic surgery |
| Keyword(2) | Surgical process analysis |
| Keyword(3) | Segmentation |
| Keyword(4) | Deep learning |
| 1st Author's Name | Shota Yamamoto |
| 1st Author's Affiliation | Nagoya University(Nagoya Univ.) |
| 2nd Author's Name | Yuichiro Hayashi |
| 2nd Author's Affiliation | Nagoya University(Nagoya Univ.) |
| 3rd Author's Name | Shintaro Morimitsu |
| 3rd Author's Affiliation | Nagoya University(Nagoya Univ.) |
| 4th Author's Name | Takuya Ozawa |
| 4th Author's Affiliation | Nagoya University(Nagoya Univ.) |
| 5th Author's Name | Takayuki Kitasaka |
| 5th Author's Affiliation | Aichi Institute of Technology(Aichi Institute of Tech.) |
| 6th Author's Name | Masahiro Oda |
| 6th Author's Affiliation | Nagoya University(Nagoya Univ.) |
| 7th Author's Name | Nobuyoshi Takeshita |
| 7th Author's Affiliation | National Cancer Center Hospital East(Cancer Center) |
| 8th Author's Name | Masaaki Ito |
| 8th Author's Affiliation | National Cancer Center Hospital East(Cancer Center) |
| 9th Author's Name | Kensaku Mori |
| 9th Author's Affiliation | Nagoya University(Nagoya Univ.) |
| Date | 2020-01-30 |
| Paper # | MI2019-115 |
| Volume (vol) | vol.119 |
| Number (no) | MI-399 |
| Page | pp.pp.209-214(MI), |
| #Pages | 6 |
| Date of Issue | 2020-01-22 (MI) |