The Institute of Electronics, Information and Communication Engineers (IEICE)
Abstract
This article is a technical report without peer review, and its polished and/or extended version may be published elsewhere.ロボット支援手術をはじめとする鏡視下手術では臓器に及ぼされる外力を正確には知ることはできず, また計測も困難である. 本研究では, 単一カメラ画像に基づく生体臓器に対する鉗子圧の推定を目指している. 3軸力覚センサを軸内に組み込んだ鉗子を製作し, 摘出臓器に対する押込操作時の鉗子圧とカメラ画像を取得した. 複数操作を対象に計測された鉗子圧データと時系列カメラ画像について同期を取った学習用データベースを構築し, 深層学習による学習と推定を行って鉗子圧の推定誤差を確認したので報告する.In laparoscopic surgery including robotic surgery, it is not possible to accurately measure the contact force applied to organs. The purpose of this study is to estimate the forceps pressure applied to an organ based on a single-viewpoint camera image. Using forceps with a three-axis pressure sensor, the forceps pressure and camera images during the pushing operation to ex-vivo organs were acquired. Synchronized dataset of forceps pressures and time-series camera images were created for multiple operations, and deep-learning was applied to confirm the estimation error of forceps pressure
