인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
피인용 0
초록·키워드
To implement accurate AR navigation, real-time AR-core transformation from the coordinate system of the camera to that of a virtual object is necessary. If feature points in the camera image and virtual object are detected robustly and paired suitably, the direct calculation of the AR-core transformation is feasible for real-time update. However, in endoscopic or microscopic surgery, determining the AR-core transformation requires feature points within the patient’s body. It is challenging and time-consuming to determine robust feature points owing to constraints such as narrow working space, featureless organ structures, and organ deformation. Consequently, direct calculation can retrieve unreliable results. Thus, a position sensor has been commonly utilized for updating the AR-core transformation indirectly in real time given its accuracy, measurement speed, and reliability. Optical trackers are widely used when implementing AR for surgical applications to compensate for camera or patient movement in real time. A rigid transformation between the image and camera frames is necessary and should be updated for real-time AR. For this purpose, two preoperative steps are essential: image-to-patient registration to represents the transformation between the image and patient frames, and hand–eye calibration to represents the transformation between the camera frame and the frame of an optical tracker marker attached to the camera. We have found an optimal solution to acquire these two transformations in one-step, achieving the high accuracy in AR display.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
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UCI(KEPA) : I410-151-26-02-094553969
