• Progress in Superconductivity
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• v.13 no.3
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• pp.139-145
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• 2012

Electric activity of cardiac muscles generates magnetic fields. Magnetocardiography (or MCG) technology, measuring these magnetic signals, can provide useful information for the diagnosis of heart diseases. It is already about 40 years ago that the first measurement of MCG signals was done by D. Cohen using SQUID (superconducting quantum interference device) sensor inside a magnetically shielded room. In the early period of MCG history, bulky point-contact RF-SQUID was used as the magnetic sensor. Thanks to the development of Nb-based Josephson junction technology in mid 1980s and new design of tightly-coupled DC-SQUID, low-noise SQUID sensors could be developed in late 1980s. In around 1990, several groups developed multi-channel MCG systems and started clinical study. However, it is quite recent years that the true usefulness of MCG was verified in clinical practice, for example, in the diagnosis of coronary artery disease. For the practical MCG system, technical elements of MCG system should be optimized in terms of performance, fabrication cost and operation cost. In this review, development history, technical issue, and future development direction of MCG technology are described.

• Journal of Korea Game Society
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• v.11 no.6
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• pp.3-11
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• 2011

The sound of digital media would be able to perform communication by stimulating body's senses. Because the sound stimuli could arouse a person into the physiological excitement and sensitivity, which appear as the changes of heartbeat, blood pressure, brain waves(EEG) signals. In this paper, we would like to examine whether the game music mixed with relaxing white noises has an effect to relax game player or not through the EEG changes of game players. For the experiment, we divided game players into group A that plays game while hearing game music mixed with white noises, and group B that plays game while hearing game music not mixed. And we measured the EEG changes of the prefrontal lobe between two groups. The result shows that the game music mixed with white noises has an relaxing effect for the left brain, but fall short of the expectations for the right brain. It would be a basic research which will contribute to the development of serious games for psychotherapy using relaxing white noises.

• Journal of the Korean Society of Radiology
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• v.13 no.5
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• pp.705-711
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• 2019

Currently, the brain CT scan of the latest equipment lacks the study of parameter change and dose change and especially of noise, uniformity analysis and dose change. Therefore, this study attempted to study the phenomenon that occurs at this time by analyzing tube voltage, slice thickness, and pitch change in exposure parameters when using high specification CT. Experimental results show that uniformity is better when using high voltage, thick slice thickness selection, and minimum pitch. As a result of the combination, the most uniformity condition was 140 kVp, 10 mm and pitch 0.5. Noise was found to be improved regardless of pitch by increasing tube voltage and slice thickness. The radiation dose increased linearly with tube voltage and pitch. Therefore, the results of this study will serve as a reference for the use of High specification brain CT.

• Korean Journal of Cognitive Science
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• v.21 no.2
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• pp.309-338
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• 2010

In this paper, we studied the brain-computer interface (BCI). BCIs help severely disabled people to control external devices by analyzing their brain signals evoked from motor imageries. The findings in the field of neurophysiology revealed that the power of $\beta$(14-26 Hz) and $\mu$(8-12 Hz) rhythms decreases or increases in synchrony of the underlying neuronal populations in the sensorymotor cortex when people imagine the movement of their body parts. These are called Event-Related Desynchronization / Synchronization (ERD/ERS), respectively. We implemented a BCI-based mouse interface system which enabled subjects to control a computer mouse cursor into four different directions (e.g., up, down, left, and right) by analyzing brain signal patterns online. Tongue, foot, left-hand, and right-hand motor imageries were utilized to stimulate a human brain. We used a non-invasive EEG which records brain's spontaneous electrical activity over a short period of time by placing electrodes on the scalp. Because of the nature of the EEG signals, i.e., low amplitude and vulnerability to artifacts and noise, it is hard to analyze and classify brain signals measured by EEG directly. In order to overcome these obstacles, we applied statistical machine-learning techniques. We could achieve high performance in the classification of four motor imageries by employing Common Spatial Pattern (CSP) and Linear Discriminant Analysis (LDA) which transformed input EEG signals into a new coordinate system making the variances among different motor imagery signals maximized for easy classification. From the inspection of the topographies of the results, we could also confirm ERD/ERS appeared at different brain areas for different motor imageries showing the correspondence with the anatomical and neurophysiological knowledge.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.05
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• pp.68-70
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• 1995

A low-noise pre-amplifier is developed for use in Topographic Brain Mapping system. It consists of signal generator, signal amplifier with a impedance converter, shield driver, body driver, differential amplifier, and isolation amplifier. Pre-amplifier circuit is designed with the concept of isolation and active body and shield driver. This amplifier shows the good noise behavior, high CMRR, high input impedance, low leakage current and high IMRR.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4336-4354
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• 2018

Fuzzy C-means (FCM) algorithm is a most usually technique for medical image segmentation. But conventional FCM fails to perform well enough on magnetic resonance imaging (MRI) data with the noise and intensity inhomogeneity (IIH). In the paper, we propose a Gamma correction conditional FCM algorithm with spatial information (GcsFCM) to solve this problem. Firstly, the pre-processing, Gamma correction, is introduced to enhance the details of images. Secondly, the spatial information is introduced to reduce the effect of noise. Then we introduce the effective neighborhood mechanism into the local space information to improve the robustness for the noise and inhomogeneity. And the mechanism describes the degree of participation in generating local membership values and building clusters. Finally, the adjustment mechanism and the spatial information are combined into the weighted membership function. Experimental results on four image volumes with noise and IIH indicate that the proposed GcsFCM algorithm is more effective and robust to noise and IIH than the FCM, sFCM and csFCM algorithms.

• Investigative Magnetic Resonance Imaging
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• v.11 no.2
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• pp.87-94
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• 2007

Purpose: The purpose of this study was to evaluate the usefulness of fast inversion recovery (FIR) and magnetization-prepared three dimensional gradient echo sequence (3D GRE) T1-weighted sequences for neonatal brain imaging compared with spin echo (SE) sequence in a 3T MR unit. Materials and Methods: T1-weighted axial SE, FIR and 3D GRE sequences were evaluated from 3T brain MR imaging in 20 neonates. The signal-to-noise ratio (SNR) of different tissues was measured and contrast-to-noise ratios (CNR) were determined and compared in each of the sequences. Visual analysis was carried out by grading gray-white matter differentiation, myelination, and artifacts. The Wilcoxon signed ranked test was used for evaluation of the statistical significance of CNR differences between the sequences. Results: Among the three sequences, the 3D GRE had the best SNRs. CNRs obtained with FIR and 3D GRE were statistically superior to those obtained with SE; these CNRs were better on the 3D GRE compared to the FIR. Gray to white matter differentiation and myelination were better delineated on the FIR and 3D GRE than the SE. However, motion artifacts were more commonly observed on the 3D GRE and flow-related artifacts of vessels were frequently seen on the FIR. Conclusion: FIR and 3D GRE are valuable alternative T1-weighted sequences to conventional SE imaging of the neonatal brain at 3T providing superior image quality.

• 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.

• Journal of Science Education
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• v.34 no.1
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• pp.113-123
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• 2010

The purpose of this study is to survey its characteristics through analyzing brain-wave activity in the scientifically-gifted and general children in the problem-solving process. The subjects of this study were 6 elementary school students, who are attending the institute of education for the gifted belonging to the regional office of education and 6 general children in the same region. The analysis was performed targeting total 12 people. As the task for measuring brain wave is Hanio tower, it is the effective task of researching into the problem-solving process. As the equipment of measuring brain wave is EEG System, it used equipment that was developed in Australia. The analysis of data was minimized noise. As a result of research, the gifted children are excellent in stable level compared to general people in a stable situation with opening the eyes, thereby being able to be known to be high in preparatory level for learning. This can be seen to be indicated as a result that the effect of learning is excellent due to being high in preparatory level for solving problem. Also, even in the process of performing task, the brain-activity level in the gifted children is high, thereby having been able to know that ${\alpha}-wave$ is formed that is significantly high in the regions of frontal lobe and occipital lobe. Accordingly, given developing task that is high in brain activity level of the gifted children, the higher educational effect will be able to be expected.

• Journal of radiological science and technology
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• v.42 no.2
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• pp.113-117
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• 2019

The purpose of this study was to investigate the FA value which can produce the best T2-weighted images by measuring the signal intensity and noise according to the FA value change in the brain image and the abdominal image of the mouse using micro-MRI. Brain imaging and abdominal imaging of BALB / C mice weighing 20g were performed using 4.7T (Bruker BioSpin MRI GmbH) micro-MRI equipment, Turbo RARE-T2 (spin echo-T2) images were scanned at TR 3500 msec and TE 36 msec. The changes of the FA values were $60^{\circ}$, $80^{\circ}$, $100^{\circ}$, $120^{\circ}$, $140^{\circ}$, $160^{\circ}$ and $180^{\circ}$. We measured signal intensity according to FA values of ventricle and thalamus in brain imaging, The signal intensity of kidney and muscle around the kidney was measured in abdominal images. To obtain SNR and CNR, we measured the background signals of two different parts, not the tissue. In the brain (thalamus) image, the signal intensity of FA $100^{\circ}$ was 7,433 and SNR (6.49) was the highest. In the abdominal (kidney) image, the signal intensity was highest at 16,523 when FA was $120^{\circ}$, and the highest SNR was 8.54 when FA was $140^{\circ}$. The CNR value of the brain image was 1.38 at FA $60^{\circ}$ and gradually increased to 8.29 at FA $180^{\circ}$. The CNR value of the muscle adjacent to the kidney gradually increased from 2.36 when the FA value was $60^{\circ}$ and the highest value was 4,57 at the FA value $180^{\circ}$.