• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 2002년도 Proceedings
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• pp.363-364
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• 2002

We describe quadrature type surface coil for functional magnetic resonance imaging at 3T MRI system. The coil consisted of two coplanar resonators and was used as both transmitter and receiver. The signal-to-noise ratio (SNR) of the coil was compared with that of a standard birdcage head coil. Visual cortex activation on normal subjects using LED flicker was performed. The SNR of surface coil was found to be better than that of the conventional head coil.

• International Journal of Contents
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• 제8권4호
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• pp.56-63
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• 2012

In recent decades, analyzing the activities of human brain achieved some accomplishments by using the functional Magnetic Resonance Imaging (fMRI) technique. fMRI data provide a sequence of three-dimensional images related to human brain's activity which can be used to detect instantaneous cognitive states by applying machine learning methods. In this paper, we propose a new approach for distinguishing human's cognitive states such as "observing a picture" versus "reading a sentence" and "reading an affirmative sentence" versus "reading a negative sentence". Since fMRI data are high dimensional (about 100,000 features in each sample), extremely sparse and noisy, feature selection is a very important step for increasing classification accuracy and reducing processing time. We used the Fisher Discriminant Ratio to select the most powerful discriminative features from some Regions of Interest (ROIs). The experimental results showed that our approach achieved the best performance compared to other feature extraction methods with the average accuracy approximately 95.83% for the first study and 99.5% for the second study.

• PNF and Movement
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• 제20권2호
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• pp.235-241
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• 2022

Purpose: The purpose of this study was to identify the effects of low intensity blood flow restriction training (LBFR) on the central nervous system of healthy adults. Methods: Ten healthy right-handed adults (eight males and two females, mean age of 28.6 ± 2.87 years) were selected as study subjects. Functional magnetic resonance imaging (fMRI) was conducted to measure brain activation (BA) following LBFR and non-LBFR. The primary motor area, premotor area, and supplementary motor area, which are closely related to exercise, were set as the regions of interest. Results: The BA recorded during the LBFR condition was 931.7 ± 302.44 voxel, and the BA recorded during the non-LBFR condition was 1,510.9 ± 353.47 voxel. Conclusion: BA was lower during LBFR than during non-LBFR.

• Investigative Magnetic Resonance Imaging
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• 제16권2호
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• pp.136-141
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• 2012

목적: 정상인에서 항혈소판제제인 클로피도그렐이 손운동기능 과제를 수행하는 동안 운동기능의 생리학적 반응에 대한 약리적 조절효과를 알아보고자 하였다. 대상과 방법: 10명의 오른손잡이 정상인을 대상으로 클로피도그렐 사용전, 최대 복용량 복용후, 정상상태 유지시로 세번에 걸쳐 뇌기능 자기공명영상 데이터를 획득하였다. 운동과제로는 주먹을 쥐었다 폈다하는 운동을 시행하였고 3.0 테슬라 자기공명영상기기에서 혈액산소의존성(BOLD) 대조도를 획득하였으며 이를 위하여 $T2^*$ 강조 EPI 영상기법을 사용하였다. 뇌기능 자기공명영상 데이터의 영상전처리 및 통계분석은 SPM2를 사용하였다. 결과: 이차수준 분석에서 주운동영역을 포함하는 편측 감각운동중추의 활성화가 나타났다. 클로피도그렐 사용전의 활성화 화소수는 173, 최대 복용량 복용후 활성화 화소수는 1049, 정상상태 유지시 활성화 화소수는 673 이었다. 최대 T값을 기준으로 측정한 BOLD 신호의 강도변화는 관찰되지 않았다. 결론: 본 연구결과는 클로피도그렐에 의해 대뇌 운동 활성이 조절된다는 사실과 또한 뇌기능 자기공명영상이 이러한 변화를 감지할수 있을만큼 높은 민감성을 가진다는 사실을 제안하고 있다.

• 한국지능시스템학회논문지
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• 제17권6호
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• pp.832-837
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• 2007

많은 연구자들은 인간의 사고를 functional Magnetic Resonance Imaging (fMRI), Time Resolved Spectroscopy(TRS), Electroencephalography(EEG)등을 이용해서 두뇌 활동 영역을 연구하고 있다. 주로 의학 분야와 심리학의 영역에서 두뇌의 활동을 연구하여 간질이나 발작을 알아내고 거짓말 탐지 분야에서도 사용된다. 본 논문에서는 사람의 두뇌활동을 측정하여 인간의 감정을 인식하는 연구에 중점을 두었다. 특히, fMRI와 TRS 그리고 EEG를 이용해서 사람의 두뇌 활동을 측정하는 연구를 하였다. 많은 연구자들이 한 가지 측정 장치만을 사용하여서 측정하거나 fMRI와 EEG를 동시에 측정하는 연구를 진행하고 있다. 현재에는 단순히 두뇌의 활동을 측정하거나 측정 시 발생하는 잡음들을 제거하는 연구들에 중점을 두고 진행되고 있다. 본 연구에서는 fMRI와 TRS를 동시에 측정하여 얻은 두뇌 활동 데이터를 가지고 감정에 따른 활동영역의 EEG 신호를 측정하였다. EEG 신호분석에 있어서 기존의 뇌파만을 가지고 특징을 찾아내는 것을 넘어서 각각의 채널에서 기록되는 뇌파의 파형을 주파수에 따라서 분류하고 정확한 측정을 위해 낮은 주파수를 제거하고 연구자가 필요한 부분의 뇌파를 분석하였다.

• 대한자기공명의과학회:학술대회논문집
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• 대한자기공명의과학회 2000년도 제5차 추계학술대회
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• pp.40-41
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• 2000

• 대한자기공명의과학회:학술대회논문집
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• 대한자기공명의과학회 2000년도 제5차 추계학술대회
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• pp.43-43
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• 2000

• 생물정신의학
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• 제25권1호
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• pp.1-8
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• 2018

Insomnia is a common sleep-related symptom which occurs in many populations, however, the neural mechanism underlying insomnia is not yet known. The hyperarousal model explains the neural mechanism of insomnia to some extent, and the frontal cortex dysfunction has been known to be related to primary insomnia. In this review, we discuss studies that applied resting state and/or task-related functional magnetic resonance imaging to demonstrate the deficits/dysfunctions of functional activation and network in primary insomnia. Empirical evidence of the hyperarousal model and proposed relation between the frontal cortex and other brain regions in primary insomnia are examined. Reviewing these studies could provide critical insights regarding the pathophysiology, brain network and cerebral activation in insomnia and the development of novel methodologies for the diagnosis and treatment of insomnia.

• Communications for Statistical Applications and Methods
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• 제27권6호
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• pp.603-624
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• 2020

There is an emerging interest in brain functional connectivity (FC) based on functional Magnetic Resonance Imaging in Alzheimer's disease (AD) studies. The complex and high-dimensional structure of FC makes it challenging to explore the association between altered connectivity and AD susceptibility. We develop a pipeline to refine FC as proper covariates in a penalized logistic regression model and classify normal and AD susceptible groups. Three different quantification methods are proposed for FC refinement. One of the methods is dimension reduction based on common component analysis (CCA), which is employed to address the limitations of the other methods. We applied the proposed pipeline to the Alzheimer's Disease Neuroimaging Initiative (ADNI) data and deduced pathogenic FC biomarkers associated with AD susceptibility. The refined FC biomarkers were related to brain regions for cognition, stimuli processing, and sensorimotor skills. We also demonstrated that a model using CCA performed better than others in terms of classification performance and goodness-of-fit.

• Biomolecules & Therapeutics
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• 제26권1호
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• pp.81-92
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• 2018

It is widely accepted that altered metabolism contributes to cancer growth and has been described as a hallmark of cancer. Our view and understanding of cancer metabolism has expanded at a rapid pace, however, there remains a need to study metabolic dependencies of human cancer in vivo. Recent studies have sought to utilize multi-modality imaging (MMI) techniques in order to build a more detailed and comprehensive understanding of cancer metabolism. MMI combines several in vivo techniques that can provide complementary information related to cancer metabolism. We describe several non-invasive imaging techniques that provide both anatomical and functional information related to tumor metabolism. These imaging modalities include: positron emission tomography (PET), computed tomography (CT), magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS) that uses hyperpolarized probes and optical imaging utilizing bioluminescence and quantification of light emitted. We describe how these imaging modalities can be combined with mass spectrometry and quantitative immunochemistry to obtain more complete picture of cancer metabolism. In vivo studies of tumor metabolism are emerging in the field and represent an important component to our understanding of how metabolism shapes and defines cancer initiation, progression and response to treatment. In this review we describe in vivo based studies of cancer metabolism that have taken advantage of MMI in both pre-clinical and clinical studies. MMI promises to advance our understanding of cancer metabolism in both basic research and clinical settings with the ultimate goal of improving detection, diagnosis and treatment of cancer patients.