| Presentation | 2021-03-15 Feasibility study of automatic extraction method of coronary artery stationary period using CNN Remina Kasai, Yuta Endo, Haruna Shibou, Makoto Amanuma, Kuninori Kobayashi, Shigehide Kuhara, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Magnetic resonance coronary angiography (MRCA) requires data acquisition during the stationary period of the coronary arteries． Therefore， accurate detection of this period is important． However， it is currently time-consuming and operator-dependent， because it is visually determined from Cine images． To automatically extract the stationary period， a template-matching method has been developed for tracking the coronary artery position． However， owing to changes in the shape of the coronary arteries during the cardiac phase， it is difficult to detect the position of each coronary artery using a single template． We developed an automatic method to detect the stationary period of coronary arteries using a convolutional neural network (CNN) and investigated its feasibility at 1.5T and 3.0T． |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | CNN / MRI / Coronary Artery / Machine Learning |
| Paper # | MI2020-61 |
| Date of Issue | 2021-03-08 (MI) |
| Conference Information | |
| Committee | MI |
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| Conference Date | 2021/3/15(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Medical Imaging |
| 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) | Feasibility study of automatic extraction method of coronary artery stationary period using CNN |
| Sub Title (in English) | Comparison between 1.5T and 3.0T |
| Keyword(1) | CNN |
| Keyword(2) | MRI |
| Keyword(3) | Coronary Artery |
| Keyword(4) | Machine Learning |
| 1st Author's Name | Remina Kasai |
| 1st Author's Affiliation | Kyorin University(Kyorin Univ.) |
| 2nd Author's Name | Yuta Endo |
| 2nd Author's Affiliation | Kyorin University(Kyorin Univ.) |
| 3rd Author's Name | Haruna Shibou |
| 3rd Author's Affiliation | Kyorin University(Kyorin Univ.) |
| 4th Author's Name | Makoto Amanuma |
| 4th Author's Affiliation | Kyorin University(Kyorin Univ.) |
| 5th Author's Name | Kuninori Kobayashi |
| 5th Author's Affiliation | Kyorin University(Kyorin Univ.) |
| 6th Author's Name | Shigehide Kuhara |
| 6th Author's Affiliation | Kyorin University(Kyorin Univ.) |
| Date | 2021-03-15 |
| Paper # | MI2020-61 |
| Volume (vol) | vol.120 |
| Number (no) | MI-431 |
| Page | pp.pp.66-70(MI), |
| #Pages | 5 |
| Date of Issue | 2021-03-08 (MI) |