김형건 교수
Hyungkeon Kim
성균관대학교 바이오메카트로닉스학과 · 의학
연구실 소개
김형건 교수의 연구실은 심장판막의 생체역학적 거동과 장기적인 내구성을 해석하기 위해 고도화된 유한요소해석 및 개인화된 컴퓨터 시뮬레이션 기반의 심장판막 수술 전후 평가를 주요 연구 분야로 삼고 있습니다. 특히 생체 조직의 비선형 이방성 물성 특성을 정밀하게 모델링하여, 판막의 기계적 응력 분포와 조직 변형을 분석함으로써 구조적 퇴행과 칼슘 침착의 원인을 규명하고자 합니다. 또한, 뇌 내 신경전달물질 분석 및 농업 분야의 약한 감독 기반 영상 세그멘테이션 기술 등 다학제적 접근을 통해 의료 및 농업 분야의 정밀의료와 스마트 기술 응용을 선도하고 있습니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15While providing nearly trouble-free function for 10-12 years, current bioprosthetic heart valves (BHV) continue to suffer from limited long-term durability. This is usually a result of leaflet calcification and/or structural degeneration, which may be related to regions of stress concentration associated with complex leaflet deformations. In the current work, a dynamic three-dimensional finite element analysis of a pericardial BHV was performed with a recently developed FE implementation of the
A simple and rapid liquid chromatography tandem mass spectrometry method has been developed for the determination of BH4, DA, 5-HT, NE, EP, Glu, and GABA in mouse brain using epsilon-acetamidocaproic acid and isotopically labeled neurotransmitters as internal standards. Proteins in the samples were precipitated by adding acetonitrile, and then the supernatants were separated by a Sepax Polar-Imidazole (2.1 mm × 100 mm, i.d., 3 μm) column by adding a mixture of 10 mM ammonium formate in acetonitr
Posterior leaflet prolapse following chordal elongation or rupture is one of the primary valvular diseases in patients with degenerative mitral valves (MVs). Quadrangular resection followed by ring annuloplasty is a reliable and reproducible surgical repair technique for treatment of posterior leaflet prolapse. Virtual MV repair simulation of leaflet resection in association with patient-specific 3D echocardiographic data can provide quantitative biomechanical and physiologic characteristics of
Machine vision with deep learning is a promising type of automatic visual perception for detecting and segmenting an object effectively; however, the scarcity of labelled datasets in agricultural fields prevents the application of deep learning to agriculture. For this reason, this study proposes weakly supervised crop area segmentation (WSCAS) to identify the uncut crop area efficiently for path guidance. Weakly supervised learning has advantage for training models because it entails less labor
In order to overcome the current limitations in current threshold-based and machine learning-based fall detectors, an insole system and novel fall classification model were created. Because high-acceleration activities have a high risk for falls, and because of the potential damage that is associated with falls during high-acceleration activities, four low-acceleration activities, four high-acceleration activities, and eight types of high-acceleration falls were performed by twenty young male su
This study demonstrates specific highlighting of early/inflammatory atheroma in vivo using anti-ICAM-1 ELIP. Three-dimensional IVUS reconstruction provides good visualization of plaque distribution in the arterial wall. This novel methodology may help to detect and diagnose pathophysiologic development of all stages of atheroma formation in vivo and quantitate plaque volume for serial and long-term atherosclerotic treatment studies.
대표 연구 분야
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