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승성민(Sungmin Seung),강병전(Byungjeon Kang),박석호(Sukho Park),박종오(Jongoh Park),김경환(Kyunghwan Kim) 대한기계학회 2009 대한기계학회 춘추학술대회 Vol.2009 No.5
Recently, due to the remarkable progress of robot technologies, many robots are applied to various applications. Especially, for the requests of the high quality medical service, the interests of medical robot rapidly increased. The area of medical robot system is classified into surgical robot, surgical assisting robot, surgical simulator and rehabilitation robot. This paper suggested a teleoperation surgical robot system for a minimally invasive brain surgery. The propose robot system consists of 4 DOF master system and 4 DOF slave manipulator, which are driven by electrical motors and tendon mechanism. The haptic feedback in master system can be realized and thus the precise manipulation of the slave system is possible. For the minimally invasive brain surgery, the miniaturized slave manipulator is designed fabricated. The slave system and the master control system are connected by TCP/IP communication and the slave system can be remotely controlled by the master system.
MRI 영상 유도 수술 로봇을 위한 개선된 군집 분석 방법을 이용한 뇌종양 영역 검출 개발
김대관,차경래,승성민,정세미,최종균,노지형,박충환,송태하,Kim, DaeGwan,Cha, KyoungRae,Seung, SungMin,Jeong, Semi,Choi, JongKyun,Roh, JiHyoung,Park, ChungHwan,Song, Tae-Ha 대한의용생체공학회 2019 의공학회지 Vol.40 No.3
Brain tumor surgery may be difficult, but it is also incredibly important. The technological improvements for traditional brain tumor surgeries have always been a focus to improve the precision of surgery and release the potential of the technology in this important area of the body. The need for precision during brain tumor surgery has led to an increase in Robotic-assisted surgeries (RAS). One of the challenges to the widespread acceptance of RAS in the neurosurgery is to recognize invisible tumor accurately. Therefore, it is important to detect brain tumor size and location because surgeon tries to remove as much tumor as possible. In this paper, we proposed brain tumor detection procedures for MRI (Magnetic Resonance Imaging) system. A method of automatic brain tumor detection is needed to accurately target the location of the lesion during brain tumor surgery and to report the location and size of the lesion. In the qualitative assessment, the proposed method showed better results than those obtained with other brain tumor detection methods. Comparisons among all assessment criteria indicated that the proposed method was significantly superior to the threshold method with respect to all assessment criteria. The proposed method was effective for detecting brain tumor.