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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.
박충환(Chunghan Park),신윤호(Yunho Shin),김대관(Daegwan Kim),홍주현(Juhyun Hong) 대한전자공학회 2018 대한전자공학회 학술대회 Vol.2018 No.6
This paper describes the implementation of bio-signals measurement module for multi-purpose medical platform system. Purposed module consists of a low-frequency bio-signal measurement board, a broadband high-frequency bio-signal measurement board, and a bio-signal data control and transmitter board. You can use this module to measure electroencephalogram(EEG), electromyograph(EMG), electrocardiogram(ECG), photoplethysmogram(PPG) signals. After obtaining the measured values by contacting the sensor with the body, it is transferred to the PC using a serial communication. The measurement result is received, we shows values of the biological signal of the user corresponding to each sensor. Future studies will be aimed at studying real-time patients monitoring system. Future work should include upgrading of the modules of bio-signal processing.