• Proceedings of the Korea Information Processing Society Conference
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• 2003.11a
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• pp.511-514
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• 2003

본 연구는 입력된 영상으로부터 특정한 형태를 이루고 있는 대상 물체를 추출함에 있어, 처리에 소요되는 시간 비용(Time cost)을 줄이는 것을 목적으로 하고 있다. 이를 위하여 특정 관심 지역(Region of Interest)이나 대상 물체(Tareet object)의 경계 검출(Boundary detection)을 하는 과정에 통계학적 수치자료(SSM : Statistical Shape Model)를 사용한 접근법을 이용하였다. 또한, 향후 연구 방향인 의료 영상해석(Medical image analysis)으로의 확장성을 고려, 의료 영상 해석에 많이 사용되어지는 MRI, CT, X-Ray 이미지가 Gray level 영상이라는 것을 감안하여 Gray level 영상을 연구 대상으로 삼았다.

• Proceedings of the Korean Society of Veterinary Clinics Conference
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• 2008.10a
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• pp.155-155
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• 2008

• 한국전산유체공학회:학술대회논문집
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• 2008.03a
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• pp.181-185
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• 2008

In this study, we attempted to quantify the relative importance of assumptions regarding blood rheology. Three patient-specific carotid bifurcation geometries and time-varying flow rates were obtained using magnetic resonance imaging. For each subject, CFD simulations were carried out assuming two different non-Newtonian rheology models Carreau and Ballyk models) and rescaled Newtonian viscosities based on characteristic shear rates to account for the shear-thinning property of blood. The sensitivity of WSS and oscillatory shear index (OSI) were contextualized with respect to the reproducibility of the reconstructed geometry and to assumptions regarding the inlet boundary conditions. We conclude that the assumption of Newtonian fluid is reasonable for studies aimed at quantifying the distribution of WSS-based extrema in an image-based CFD model of carotid bifurcation.

• 한국전산유체공학회:학술대회논문집
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• 2008.10a
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• pp.181-185
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• 2008

In this study, we attempted to quantify the relative importance of assumptions regarding blood rheology. Three patient-specific carotid bifurcation geometries and time-varying flow rates were obtained using magnetic resonance imaging. For each subject, CFD simulations were carried out assuming two different non-Newtonian rheology models (Carreau and Ballyk models) and rescaled Newtonian viscosities based on characteristic shear rates to account for the shear-thinning property of blood. The sensitivity of WSS and oscillatory shear index (OSI) were contextualized with respect to the reproducibility of the reconstructed geometry and to assumptions regarding the inlet boundary conditions. We conclude that the assumption of Newtonian fluid is reasonable for studies aimed at quantifying the distribution of WSS-based extrema in an image-based CFD model of carotid bifurcation.

• International Journal of Knowledge Content Development & Technology
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• v.3 no.1
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• pp.19-29
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• 2013

Insights from the recent wealth of popular books on neuroscience are offered to suggest a strengthening of theory in information science. Information theory has traditionally neglected the human dimension in favour of 'scientific' theory often derived from the Shannon-Weaver model. Neuroscientists argue in excitingly fresh ways from the evidence of case studies, non-intrusive experimentation and the measurements that can be obtained from technologies that include electroencephalography, positron emission tomography (PET), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG). The way in which the findings of neuroscience intersect with ideas such as those of Kahneman on fast and slow thinking and Csikszentmihalyi on flow, is tentatively explored as lines of connection with information science. It is argued that the beginnings of a theoretical underpinning for current web-based information searching in relation to established information retrieval methods can be drawn from this.

• Proceedings of the KSMRM Conference
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• 2002.11a
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• pp.114-114
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• 2002

Purpose： To know the fate of Gadophrin-2-enhanced areas in hearts with acute reperfused myocardial infarction. Method： The left anterior descending branches of coronary arteries were occluded for 90 min and reperfused for 60 min in 15 rabbits. Then, Gadophrin-2 (0.05 mmol/kg) was injected via ear veins. Short-axial T1-weighted spin echo images and fast cine images were obtained 24 hours after injection of Gadophrin-2. After four weeks, short-axial cine MRI was performed and T1-weighted spin echo Images were obtained 5 min and 15 min after injection of Gd-DTPA (0.2 mmol/kg). The animals were sacrificed and short-axial slices of the specimen were stained with 1.5% triphenyltetrazolium chloride (TTC) solution.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.455-458
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• 2010

Extracting the brain from magnetic resonance imaging head scans is an essential preprocessing step of which the accuracy greatly affects subsequent image analysis. The currently popular Brain Extraction Tool produces a brain mask which may be too smooth for practical use to reduce the accuracy. This paper presents a novel and indirect brain extraction method based on non-brain tissue segmentation. Based on ITK, the proposed method allows a non-brain contour by using region growing to match with the original image naturally and extract the brain tissue. Experiments on two set of MRI data and 2D brain image in horizontal plane and 3D brain model indicate successful extraction of brain tissue from a head.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.520-522
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• 2022

의료 인공지능은 특정 진단에서 높은 정확도를 보이지만 모델의 신뢰성 문제로 인해 활발하게 쓰이지 못하고 있다. 이에 따라 인공지능 모델의 진단에 대한 원인 설명의 필요성이 대두되었고 설명가능한 의료 인공지능에 관한 연구가 활발히 진행되고 있다. 하지만 MRI 등 의료 영상 인공지능 분야에서 주로 진행되고 있으며, 이미지 형태가 아닌 전자의무기록 데이터 (Electronic Health Record, EHR) 를 기반으로 한 모델의 설명가능성 연구는 EHR 데이터 자체의 복잡성 때문에 활발하게 진행 되지 않고 있다. 본 논문에서는 전자의무기록 데이터인 MIMIC-III (Medical Information Mart for Intensive Care) 를 전처리 및 그래프로 표현하고, GCT (Graph Convolutional Transformer) 모델을 학습시켰다. 학습 후, 어텐션 흐름 그래프를 시각화해서 모델의 예측에 대한 직관적인 설명을 제공한다.

• Journal of the Korean Society of Radiology
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• v.83 no.3
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• pp.750-750
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• 2022

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1760-1778
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• 2018

For image segmentation with intensity inhomogeneity, many region-based level set methods have been proposed. Some of them however can't get the relatively ideal segmentation results under the severe intensity inhomogeneity and weak edges, and without use of the image gradient information. To improve that, we propose a new level set method combined with local direction gradient in this paper. Firstly, based on two assumptions on intensity inhomogeneity to images, the relationships between segmentation objects and image gradients to local minimum and maximum around a pixel are presented, from which a new pixel classification method based on weight of Euclidian distance is introduced. Secondly, to implement the model, variational level set method combined with image spatial neighborhood information is used, which enhances the anti-noise capacity of the proposed gradient information based model. Thirdly, a new diffusion process with an edge indicator function is incorporated into the level set function to classify the pixels in homogeneous regions of the same segmentation object, and also to make the proposed method more insensitive to initial contours and stable numerical implementation. To verify our proposed method, different testing images including synthetic images, magnetic resonance imaging (MRI) and real-world images are introduced. The image segmentation results demonstrate that our method can deal with the relatively severe intensity inhomogeneity and obtain the comparatively ideal segmentation results efficiently.