• Journal of Biomedical Engineering Research
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• v.22 no.5
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• pp.377-384
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• 2001

Generally. there have been limitations to investigate structural brain abnormalities with MR images for psychiatric patients. such as schizophrenia. depression and autism, since the brain abnormalities of psychiatric Patients are too small to be detected easily. It has been suggested to exploit the result of size-comparison or analysis of specified Part in various brain tissues. Results of brain analysis highly depend on accuracy of the brain segmentation because it is hard to segment image that the boundary between tissues in the brain MRI is inherently value. In this Paper. we improve the quality of brain segmentation so that we increase the credit of brain analysis. In addition, we Provide the improved images for studying brain abnormalities through left-right insular volume measure using handy software tool .

• Proceedings of the Korea Society for Simulation Conference
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• 2004.05a
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• pp.118-122
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• 2004

본 논문에서는 인체의 머리 부분을 촬영한 의료 영상에서 뇌 영역만을 분할하는 방법에 대해 제시하고자 한다. 뇌의 해부학적 구조 및 기능적 이상 부위를 파악할 경우에 영상 내에 함께 보여지는 두개골과 뇌척수액 등을 제외한 대뇌피질 영역을 분할하면 보다 효과적인 정보 분석 및 진단이 가능하게 된다. 본 시스템에서는 3단계 알고리즘을 제시한다. 첫 번째 단계에서는 영상 내에 존재하는 잡음을 제거하기 위한 필터링이고, 두 번째 단계에서는 필터링된 결과에 대한 영상분할을 수행하는 것이다 이 때 정확한 결과 도출을 위하여 사용자의 인터렉션이 들어가게 된다. 세번째 단계에서는 형태학적 방법을 이용하여 분할 결과를 보완한다. 본 연구를 위한 실험에는 자기 공명 촬영 영상(MRI: Magnetic Resonance Imaging), 단일 광전자 방출 단층 촬영영상(SPECT: Single Photon Emission Computed Tomography), 양전자 방출 단층 촬영영상(PET: Positron Emission Tomography) 등을 사용하였다. 본 시스템에서는 다양한 모달리티의 뇌 영상에서 대뇌피질 부분을 정확하게 영상 분할함으로써 뇌의 구조적 이상을 판단하기 위한 해부학적 정보 분석을 가능케 하고 있다. 뿐만 아니라 뇌 질환에 대한 정확한 진단 시뮬레이션도 가능하게 하고자 한다.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.2
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• pp.69-78
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• 2016

Ischemic stroke is a disease that the brain tissues cannot function by reducing blood flow due to thrombosis or embolisms. Due to the nature of the disease, it is most important to identify the status of cerebral vessel and the medical images are necessarily used for its diagnosis. Among many indicators, brain MRI is most widely utilized because experts can effectively obtain the semantic information such as cerebral anatomy aiding the diagnosis with it. However, in case of emergency diseases like ischemic stroke, even though a intelligent system is required for supporting the prompt diagnosis and treatment, the current systems have some difficulties to provide the information of medical images intuitively. In other words, as the current systems have managed the medical images based on the basic meta-data such as image name, ID and so on, they cannot consider semantic information inherent in medical images. Therefore, in this paper, to provide core information like cerebral anatomy contained in brain MRI, we suggest a template-driven medical images mapping method. The key idea of the method is defining the mapping characteristics between anatomic feature and representative images by using template images that can be representative of the whole brain MRI image set and revealing the semantic relations that only medical experts can check between images. With our method, it will be possible to manage the medical images based on semantic.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.507-518
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• 2021

Magnetic resonance imaging (MRI) is a key technology that has been seeing increasing use in studying the structural and functional innerworkings of the brain. Analyzing the variability of brain connectome through tractography analysis has been used to increase our understanding of disease pathology in humans. However, there lacks standardization of analysis methods for small animals such as mice, and lacks scientific consensus in regard to accurate preprocessing strategies and atlas-based neuroinformatics for images. In addition, it is difficult to acquire high resolution images for mice due to how significantly smaller a mouse brain is compared to that of humans. In this study, we present an Allen Mouse Brain Atlas-based image data analysis pipeline for structural connectivity analysis involving structural region segmentation using mouse brain structural images and diffusion tensor images. Each analysis method enabled the analysis of mouse brain image data using reliable software that has already been verified with human and mouse image data. In addition, the pipeline presented in this study is optimized for users to efficiently process data by organizing functions necessary for mouse tractography among complex analysis processes and various functions.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.323-328
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• 2004

The development of group-specific tissue probability maps (TPM) provides a priori knowledge for better result of cerebral tissue classification with regard to the inter-ethnic differences of inter-subject variability. We present sequential procedures of group-specific TPM and evaluate the age effects in the structural differences of TPM. We investigated 100 healthy volunteers with high resolution MRI scalming. The subjects were classified into young (60, 25.92+4.58) and old groups (40, 58.83${\pm}$8.10) according to the age. To avoid any bias from random selected single subject and improve registration robustness, average atlas as target for TPM was constructed from skull-stripped whole data using linear and nonlinear registration of AIR. Each subject was segmented into binary images of gray matter, white matter, and cerebrospinal fluid using fuzzy clustering and normalized into the space of average atlas. The probability images were the means of these binary images, and contained values in the range of zero to one. A TPM of a given tissue is a spatial probability distribution representing a certain subject population. In the spatial distribution of tissue probability according to the threshold of probability, the old group exhibited enlarged ventricles and overall GM atrophy as age-specific changes, compared to the young group. Our results are generally consistent with the few published studies on age differences in the brain morphology. The more similar the morphology of the subject is to the average of the population represented by the TPM, the better the entire classification procedure should work. Therefore, we suggest that group-specific TPM should be used as a priori information for the cerebral tissue classification.

• Journal of Biomedical Engineering Research
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• v.20 no.3
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• pp.283-290
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• 1999

Because MR(Magnetic Resonance) slice images have much information of functions about body organs, it is very effeclive for diagnoses lo analyze and visualize MR slice images. A visuahzation process is composed of medical image acquisition, preprocessmg, segmentation, inlerpolation, rendering. Segmentation and interpolation among thenl ,1re currenl hot topics because of MR slice image imperfections. This paper proposes a method for segmentalion, mlerpolation respectively and addresses 3 D-visualizmg of a head. We segmented head tissues uomg otructural knowledge of head studied by clinical experiments sequentially. We improved the dynamic elastic inlerpolation to Utilize in concave conlour. We compared the proposed segmentation method and the interpolation method with other methods.

• The KIPS Transactions:PartA
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• v.13A no.5 s.102
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• pp.465-472
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• 2006

Recently, many suggestions have been made in image segmentation methods for extracting human organs or disease affected area from huge amounts of medical image datasets. However, images from some areas, such as brain, which have multiple structures with ambiruous structural borders, have limitations in their structural segmentation. To address this problem, clustering technique which classifies voxels into finite number of clusters is often employed. This, however, has its drawback, the influence from noise, which is caused from voxel by voxel operations. Therefore, applying image enhancing method to minimize the influence from noise and to make clearer image borders would allow more robust structural segmentation. This research proposes an efficient structural segmentation method by filtering based clustering to extract detail structures such as white matter, gray matter and cerebrospinal fluid from brain MR. First, coherence enhancing diffusion filtering is adopted to make clearer borders between structures and to reduce the noises in them. To the enhanced images from this process, fuzzy c-means clustering method was applied, conducting structural segmentation by assigning corresponding cluster index to the structure containing each voxel. The suggested structural segmentation method, in comparison with existing ones with clustering using Gaussian or general anisotropic diffusion filtering, showed enhanced accuracy which was determined by how much it agreed with the manual segmentation results. Moreover, by suggesting fine segmentation method on the border area with reproducible results and minimized manual task, it provides efficient diagnostic support for morphological abnormalities in brain.

• The Korean Journal of Nuclear Medicine
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• v.38 no.3
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• pp.241-252
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• 2004

Purpose: Population based structural and functional maps of the brain provide effective tools for the analysis and interpretation of complex and individually variable brain data. Brain MRI and PET standard templates and statistical probabilistic maps based on image data of Korean normal volunteers have been developed and probabilistic maps based on cytoarchitectonic data have been introduced. A quantification method using these data was developed for the objective assessment of regional intensity in the brain images. Materials and Methods: Age, gender and ethnic specific anatomical and functional brain templates based on MR and PET images of Korean normal volunteers were developed. Korean structural probabilistic maps for 89 brain regions and cytoarchitectonic probabilistic maps for 13 Brodmann areas were transformed onto the standard templates. Brain FDG PET and SPGR MR images of normal volunteers were spatially normalized onto the template of each modality and gender. Regional uptake of radiotracers in PET and gray matter concentration in MR images were then quantified by averaging (or summing) regional intensities weighted using the probabilistic maps of brain regions. Regionally specific effects of aging on glucose metabolism in cingulate cortex were also examined. Results: Quantification program could generate quantification results for single spatially normalized images per 20 seconds. Glucose metabolism change in cingulate gyrus was regionally specific: ratios of glucose metabolism in the rostral anterior cingulate vs. posterior cingulate and the caudal anterior cingulate vs. posterior cingulate were significantly decreased as the age increased. 'Rostral anterior'/'posterior' was decreased by 3.1% per decade of age ($P<10^{-11}$, r=0.81) and 'caudal anterior'/'posterior' was decreased by 1.7% ($P<10^{-8}$, r=0.72). Conclusion: Ethnic specific standard templates and probabilistic maps and quantification program developed in this study will be useful for the analysis of brain image of Korean people since the difference in shape of the hemispheres and the sulcal pattern of brain relative to age, gender, races, and diseases cannot be fully overcome by the nonlinear spatial normalization techniques.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.05a
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• pp.295-295
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• 2004

본 연구에서는 한국인 20대 남자 50명(23$\pm$2세)과 여자 50명(20$\pm$1세)의 MR 뇌 영상을 KAIST 뇌과학 연구센터에 있는 37 MRI 기기로 획득하였고 Brain Voyager(B/V)를 이용하여 소뇌의 부피를 측정하고자 한다. 남자와 여자의 뇌의 구조가 부분적으로 차이가 있다는 것은 이미 밝혀진 사실이다 남자의 전체적인 brain volume이 약 10% 크다는 사실도 잘 알려져 있다. 그러므로 본 연구에서도 성별에 따라 소뇌의 부피의 차이가 있는지도 검증하고자 한다.(중략)

• Science of Emotion and Sensibility
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• v.15 no.4
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• pp.585-592
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• 2012

Food is crucial for the nutrition and survival of humans. Taste system is one of the fundamental senses. Taste cells detect and respond to five basic taste modalities (sweet, bitter, salty, sour, and umami). However, the cortical processing of taste sensation is much less understood. Recently, there were many efforts to observe the brain activation in response to taste stimulation using functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), and optical imaging. These different techniques do not provide directly comparable data each other, but the complementary investigations with those techniques allowed the description and understanding of the sequence of events with the dynamics of the spatiotemporal pattern of activation in the brain in response to taste stimulation. The purpose of this study is the understanding of the brain activities to taste stimuli in sensory and affective aspects and the reviewing of the recent research of the gustotopic map by functional brain mapping.