• Journal of Korea Multimedia Society
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• v.15 no.9
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• pp.1075-1085
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• 2012

In clinical research using medical images, the image segmentation is one of the most important processes. Especially, the hippocampal atrophy is helpful for the clinical Alzheimer diagnosis as a specific marker of the progress of Alzheimer. In order to measure hippocampus volume exactly, segmentation of the hippocampus is essential. However, the hippocampus has some features like relatively low contrast, low signal-to-noise ratio, discreted boundary in MRI images, and these features make it difficult to segment hippocampus. To solve this problem, firstly, We selected region of interest from an experiment image, subtracted a original image from the negative image of the original image, enhanced contrast, and applied anisotropic diffusion filtering and gaussian filtering as preprocessing. Finally, We performed an image segmentation using two level set methods. Through a variety of approaches for the validation of proposed hippocampus segmentation method, We confirmed that our proposed method improved the rate and accuracy of the segmentation. Consequently, the proposed method is suitable for segmentation of the area which has similar features with the hippocampus. We believe that our method has great potential if successfully combined with other research findings.

• Journal of Digital Contents Society
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• v.14 no.2
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• pp.275-282
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• 2013

In medical image processing field, object recognition is usually carried out by computerized processing of various input information such as brightness, shape, and pattern. If the information mentioned does not make sense, however, many limitations could occur with object recognition during computer processing. Therefore, this paper suggests effective object recognition method based on the magnetic resonance (MR) theory to resolve the basic limitations in computer processing. We propose the efficient method of robust gray-white matter segmentation by texture analysis through the Susceptibility Weighted Imaging (SWI) for contrast enhancement. As a result, an average area difference of 5.2%, which was higher than the accuracy of conventional region segmentation algorithm, was obtained.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.7A
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• pp.1006-1016
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• 2000

This study is to segment white matter, gray matter, and cerebrospinal fluid(CSF) on a brain MR image and to calculate the volume of each. First, after removing the background on a brain MR image, we segmented the whole region of a brain from a skull and a fat layer. Then, we calculated the partial volume of each component, which was present in scanning finite thickness, with the arithmetical analysis of gray value from the internal region of a brain showing the blurring effects on the basis of the MR image forming principle. Calculated partial volumes of white matter, gray matter and CSF were used to determine the threshold for the segmentation of each component on a brain MR image showing the blurring effects. Finally, the volumes of segmented white matter, gray matter, and CSF were calculated. The result of this study can be used as the objective diagnostic method to determine the degree of brain atrophy of patients who have neurodegenerative diseases such as Alzheimer's disease and cerebral palsy.

• Science of Emotion and Sensibility
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• v.12 no.4
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• pp.425-432
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• 2009

The purposes of the study were to examine cerebellar areas and lateralization responsible for visuospatial and verbal tasks using functional Magnetic Resonance Imaging(fMRI). Eight healthy male college students($21.5\;{\pm}\;2.3$ years) and eight male college students($23.3\;{\pm}\;0.5$ years) participated in this fMRI study of visuospatial and verbal tasks, respectively. Functional brain images were taken from 3T MRI using the single-shot EPI method. All functional images were aligned with anatomical images using affine transformation routines built into SPM99. The experiment consisted of four blocks. Each block included a control task(1 minute) and a cognitive task(1 minute). A run was 8 minutes long. Using the subtraction procedure, activated areas in the cerebellum during the visuospatial and verbal tasks were color-coded by t-score. A cerebellar lateralization index was calculated for both cognition tasks using number of activated voxels. The activated cerebellar regions during the both cognition tasks of this study agree with previous results. Since the number of activated voxels of the left and right cerebellar hemisphere was almost same, there was no cerebellar lateralization for both cognition tasks.

• Journal of Biomedical Engineering Research
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• v.20 no.2
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• pp.149-154
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• 1999

In anatomical aspects, magnetic resonance image offers more accurate information than other medical images such as X ray, ultrasonic and CT images. This paper introduces a method that segments and detects lesion for 2 dimensional axial MR brain images automatically. Image segmentation process consists of 2 stages. First stage extracts cerebrum region using thresholding and morphology. In the second stage, white matter, gray matter and cerebrospinal fluid in the cerebrum are extracted using FCM, We could improve processing time as removing uninterested region. Finally symmetry measure and anatomical Knowledge are used to detect lesion.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.330-334
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• 2009

본 연구는 뇌의 편측 영역 에서의 EEG(Electroencephalography) coherence 로 손동작 의도를 예측하고자 하는 연구이다. 손 동작 예측을 위한 실험에 신체에 이상이 없는 6 명의 피실험자가 참여 하였다. 실험은 데이터 트레이닝 6 분과 동작 의도 판단 6 분으로 진행되었으며 무작위 순서로 손 동작을 지시한 후 편측적 영역 5 개 지점의 EEG 와 동작 시점을 알기 위한 오른손 EMG(Electromyography)를 측정하였다. 측정된 EEG 데이터를 분석하기 위해 주파수 별 Alpha 와 Beta 를 분류하였고 EMG 신호를 기준으로 동작과 휴식으로 분류된 Alpha 와 Beta 데이터를 5 개의 측정 영역별 Coherence 분석을 하였다. 그 결과 동작과 휴식을 구분할 수 있는 통계적으로 유효한 EEG Coherence 영역을 통하여 동작 판단을 할 수 있음을 확인하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.474-476
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• 2021

Glioblastoma is the most common brain malignancies arising from glial cells. Early diagnosis and treatment plan establishment are important, and cancer is diagnosed mainly through T1CE imaging through injection of a contrast agent. However, the risk of injection of gadolinium-based contrast agents is increasing recently. Region segmentation that marks cancer regions in medical images plays a key role in CAD systems, and deep neural network models for synthesizing new images are also being studied. In this study, we propose a model that simultaneously learns the generation of T1CE images and segmentation of cancer regions. The performance of the proposed model is evaluated using similarity measurements including mean square error and peak signal-to-noise ratio, and shows average result values of 21 and 39 dB.

• 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.

• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.273-282
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• 2011

This study was to investigate the effect of improve forelimb sensorimotor function and neurotrophic factor(GAP-43) expression when differing an application time of tDCS in ischemic brain injury rat model(pre, $1^{st}$, $7^{th}$, $14^{th}$). Focal ischemic brain injury was induced in 80 Sprague-Dawley rats through middle cerebral artery occlusion(MCAO) by 'Longa' method. And then experimental groups were randomly divided into four groups; GroupI: MCAO induction, GroupII: application of tDCS(10 min) after MCAO induction, GroupIII: application of tDCS(20 min) after MCAO induction, GroupIV: application of tDCS(30 min) after MCAO induction. Modified limb placing test and single pellet reaching test were performed to test forelimb sensorimotor function. And the histological examination was also observed through the immunohistochemistric response of GAP-43(growth-associated protein-43) in the cerebral cortex. In modified limb placing test, groupIII(p<0.05) showed significantly improve than the other groups on $14^{th}$). day. In single pellet reaching test, groupIII(p<0.01) and groupIV(p<0.05) significantly improved on $14^{th}$) day. And in immunohistochemistric response of GAP-43, group III showed significantly positive response than the other groups on $14^{th}$ day. These results suggest that the intensity(0.1 mA)/time(20 min) condition of tDCS application has a significant impact on the sensorimotor functional recovery in focal ischemic brain injury rat models.

• The Korean Journal of Nuclear Medicine
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• v.34 no.6
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• pp.456-464
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• 2000

Purpose: To evaluate the effect of acupuncture on regional cerebral blood flow (rCBF) at acupoints suggested by oriental medicine to be related to the treatment of cerebrovascular diseases. Materials and Methods: Rest/acupuncture-stimulation Tc-99m ECD brain SPECT using a same-dose subtraction method was performed on 54 normal volunteers (34 males, 20 females, age range from 18 to 62 years) using six paradigms: acupuncture at acupoints GV. 20, GV. 26, LI. 4, ST. 36 and SP. 6. In the control study, needle location was chosen on a non-meridian focus 1 cm posterior to the right fibular head. All images were spatially normalized, and the differences between rest and acupuncture stimulation were statistically analyzed using SPM$^{(R)}$ for Windows$^{(R)}$. Results: Acupuncture applied at acupoint GV. 20 increased rCBF in both the anterior frontal lobes, the right frontotemporal lobes, and the left anterior temporal lobe and the left cerebellar hemisphere. Acupuncture at GV 26 increased rCBF in the left prefrontal cortex. Acupuncture at LI. 4 increased rCBF in the left prefrontal and both the inferior frontal lobes, and the left anterior temporal lobe and the left cerebellar hemisphere. Acupuncture at ST. 36 increased rCBF in the left anterior temporal lobe, the right inferior frontal lobes, and the left cerebellum. Acupuncture at SP. 6 increased rCBF in the left inferior frontal and anterior temporal lobes. In the control stimulation, no significant rCBF increase was observed. Conclusion: The results demonstrated a correlation between stimulation at each acupoint with increase in rCBF to the corresponding brain areas.