2017 Fiscal Year Final Research Report
Development of training-data-circulation-typed surgical assistant framework using medical big data and newly defined surgical information data format including pre- and post-operative data
| Project/Area Number |
15K21035
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Life / Health / Medical informatics
Biomedical engineering/Biomaterial science and engineering
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| Research Institution | University of Yamanashi |
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Principal Investigator |
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| Research Collaborator |
TAKAO Masaki
SATO Yoshinobu
OTAKE Yoshito
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Keywords | 計算機支援外科 / 手術計画 / ビッグデータ / 統計アトラス / 深層学習 / 術前支援 / 術後評価 / 畳み込みニューラルネットワーク |
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| Outline of Final Research Achievements |
The purpose of this study is to develop a surgical information management method including pre- and post-operative data for total hip replacement and training-data-circulation-typed surgical assistant system using medical big data. In this study, we defined XML data format which is able to handle many patients' data and implants data efficiently, and developed the surgical assistant system which equips exchangeable traning-data-set module and post-operative evaluation. In the experiments of pre-operative phase, 100 cases were applied to the proposed system and several surgical criteria of the optimal plans were compared with surgeon's plans. As a result, one criterion was significantly better than the surgeon's and all the others were almost equivalent. In the experiments of post-operative phase, 19 cases were applied for automated estimation of implant positions and we confirmed the highly accurate determination. We considered that the results showed the usefulness of the system.
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| Free Research Field |
医工学，医用画像解析
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