Sumin Song
Ewha Womans University · Medicine
About the Lab
Professor Sumin Song's research lab specializes in medical image analysis and computational modeling, with a focus on advancing diagnostic and visualization techniques for biomedical applications. The lab develops innovative algorithms for tumor segmentation in low-resolution PET and phase-contrast microscopy images, emphasizing accurate boundary detection and long-term live-cell imaging without phototoxicity. Additionally, the lab contributes to 3D visualization and modeling of anatomical structures, such as fetal ultrasound and coronary arteries, using efficient volume rendering and parametric modeling techniques. Their work bridges medical imaging, data mining, and computational modeling to support clinical decision-making and biological research.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15The objective of this study was to develop a model for predicting Korean adult consumers who frequently eat food-away-from-home. A total of 7,032 adults aged 19 years and older from the 2001 National Health and Nutrition Survey in Korea were used as subjects. The data were analyzed using a data mining procedure including logistic regression and decile analysis. The model developed in the study was proven to be valid in predicting the consumers who frequently eat food-away-from home(once a day or
In this paper, we present a region growing algorithm based on gradient magnitude for tumor segmentation from small animal PET images. The segmentation of PET images with low spatial resolution and high variations of intensity is more difficult than images with high resolution. Especially, it is not easy to detect the boundary between region of interest and abutting regions with similar intensity. We propose a region growing algorithm to extract tumor from adjacent regions with similar intensity
Since the morphology of tumor cells is a good indicator of their invasiveness, we used time-lapse phase-contrast microscopy to examine the morphology of tumor cells. This technique enables long-term observation of the activity of live cells without photobleaching and phototoxicity which is common in other fluorescence-labeled microscopy. However, it does have certain drawbacks in terms of imaging. Therefore, we first corrected for non-uniform illumination artifacts and then we use intensity dist
Tumor cell morphology is closely related to its invasiveness characteristics and migratory behaviors. An invasive tumor cell has a highly irregular shape, whereas a spherical cell is non-metastatic. Thus, quantitative analysis of cell features is crucial to determine tumor malignancy or to test the efficacy of anticancer treatment. We use phase-contrast microscopy to analyze single cell morphology and to monitor its change because it enables observation of long-term activity of living cells with
초음파 태아 영상의 실시간 입체 가시화를 위한 볼륨 렌더링 가속화 방법은 결과영상에 영향을 끼치지 않는 관심객체영역 외 빈공간을 샘플링 연산에서 제외시키는 공간도약 알고리즘이 일반적이다. 공간도약시 전처리과정에서 각 복셀에서 가장 가까이에 있는 객체의 경계복셀까지의 거리를 미리 계산저장한 거리지도를 이용하면, 반복적 샘플링 연산을 줄임으로써 렌더링 속도 효율을 높일 수 있다. 거리지도 생성에 사용되는 여러 거리계산변환법 중 거리계산이 정교할수록 실수계산으로 인한 전처리시간이 소요되는 반면, 근사계산법을 이용하면 거리값 연산의 오차로 인한 샘플링의 횟수가 증가하는 단점이 있다. 본 논문에서는 전처리시간의 지연과 샘플링 횟수의 증가를 비교하여 초음파 태아 영상의 볼륨 렌더링에 가장 적합한 거리지도를 선택한다.
본 논문은 관상동맥의 구조와 그 움직임을 사실적으로 표현하기 위한 매개변수적 모델링기법을 제안한다. 매개변수적 기법으로 생성된 모델은 메쉬 정점의 인덱스만으로 모델간 매칭을 위한 대응점을 찾을 수 있으므로, 시간대별로 달라지는 정점의 위치를 쉽게 추적함으로써 모델의 움직임을 표현할 수 있다. 그러나 이러한 기법으로 생성된 모델은 분리, 접합 등의 변형·조작이 어렵고, 트리형태 객체에 적용하기 힘든 단점이 있다. 본 논문에서는 이를 극복하기 위해 분할된 혈관영역의 골격데이타에서 찾아낸 분기점을 중심으로 Generalized Cylinder 를 이용하여 실린더 형태의 각 혈관세그먼트를 모델링 한 후, 분기영역을 3 개의 하프파이프(half pipe)와 2 개의 삼각형 패치로 연결하여 모델링하였다. 완성된 모델은 다시점 관상동맥데이터에 적용하였고, 각 시점에서 구해진 정점의 위치를 선형보간함으로써 부드러운 혈관의 움직임을 나타내었다.
In real time rendering of fetus the empty space leaping while traversing a ray is most frequently used accelerating technique. The main idea is to skip empty voxel samples which do not contribute the result image and it speeds up the rendering time by avoiding sampling data while traversing a ray in the empty region, saving a substantial number of interpolations. Calculating the distance from the nearest object boundary for every yokel can reduce the sampling operation. Among widely-well-known d
In this paper, we introduce new diagnosis tool to observe carotid artery based on ultrasonic volume data. The main components and applied algorithms of the developed diagnosis tool are explained. As one of main components, the semi-automatic segmentation method includes an effective speckle reducing filter and an automatic ROI tracking scheme. Furthermore, we present the reconstruction method that is effective for Y-typed carotid artery and the navigation path generation method that applies inte
The term molecular imaging can be broadly defined as the in vivo characterization and measurement of biologic processes at the cellular and molecular level. Optical imaging that has highly reproducibility and repetition used in molecular imaging research. in the bioluminescence imaging, animals currying the luciferase gene arc imaged with a cooled CCD(Charge-Coupled Device) camera to pick up the small number of photons transmitted through tissues. Molecular imaging analysis will allow us to obse
Research Areas
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