• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.173-176
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• 1995

We have developed a fast steady state free precession interferometry (SSFPI) technique which is useful for the fMRI (functional Magnetic Resonance Imaging). As is known, SSFP sequence with a suitable adjustment of gradient (readout) allows us to measure precession angle $\theta$ which is in turn related to the field inhomogeneity [1-3]. When the method is applied to the susceptibility effect based functional magnetic resonance imaging (fMRI), it was found that the direct susceptibility effect measurement was possible without perturbations such as the backgrounds and inflow effect. In this paper, simulation results and experimental results obtained with 2.0 Tesla MRI system are also presented.

• Korean Journal of Biological Psychiatry
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• v.11 no.1
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• pp.3-13
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• 2004

Objectives:Functional magnetic resonance imaging(fMRI) is one of the most useful techniques for assessing localized changes in cerebral blood flow and oxygenation using diverse challenge paradigms. This review presents the results of fMRI studies relating to schizophrenia. Methods:Several fMRI articles on this subject in psychiatric journals were surveyed. Results:Even with some methodological limitations, most studies showed activity differences between schizophrenics and control subjects. Conclusion:fMRI extends our understanding of the pathophysiological basis of schizophrenia and offer an opportunity for the assessment and management of its pathology.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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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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• v.8 no.4
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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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• v.20 no.2
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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.

• Korean Journal of Biological Psychiatry
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• v.25 no.1
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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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• v.27 no.6
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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.

• Korean Journal of Radiology
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• v.24 no.11
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• pp.1114-1130
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• 2023

Magnetic resonance neurography (MRN) is increasingly used to visualize peripheral nerves in vivo. However, the implementation and interpretation of MRN in the brachial and lumbosacral plexi are challenging because of the anatomical complexity and technical limitations. The purpose of this article was to review the clinical context of MRN, describe advanced magnetic resonance (MR) techniques for plexus imaging, and list the general categories of utility of MRN with pertinent imaging examples. The selection and optimization of MR sequences are centered on the homogeneous suppression of fat and blood vessels while enhancing the visibility of the plexus and its branches. Standard 2D fast spin-echo sequences are essential to assess morphology and signal intensity of nerves. Moreover, nerve-selective 3D isotropic images allow improved visualization of nerves and multiplanar reconstruction along their course. Diffusion-weighted and diffusion-tensor images offer microscopic and functional insights into peripheral nerves. The interpretation of MRN in the brachial and lumbosacral plexi should be based on a thorough understanding of their anatomy and pathophysiology. Anatomical landmarks assist in identifying brachial and lumbosacral plexus components of interest. Thus, understanding the varying patterns of nerve abnormalities facilitates the interpretation of aberrant findings.

• Biomolecules & Therapeutics
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• v.26 no.1
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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.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5599-5605
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• 2015

In oncology various imaging modalities play a crucial role in diagnosis, staging, restaging, treatment monitoring and follow up of various cancers. Stand-alone morphological imaging like computerized tomography (CT) and magnetic resonance imaging (MRI) provide a high magnitude of anatomical details about the tumor but are relatively dumb about tumor physiology. Stand-alone functional imaging like positron emission tomography (PET) and single photon emission tomography (SPECT) are rich in functional information but provide little insight into tumor morphology. Introduction of first hybrid modality PET/CT is the one of the most successful stories of current century which has revolutionized patient care in oncology due to its high diagnostic accuracy. Spurred on by this success, more hybrid imaging modalities like SPECT/CT and PET/MR were introduced. It is the time to explore the potential applications of the existing hybrid modalities, developing and implementing standardized imaging protocols and train users in nuclear medicine and radiology. In this review we discuss three existing hybrid modalities with emphasis on their technical aspects and clinical applications in oncology.