• Proceedings of the Korean Society of Computer Information Conference
• /
• 2019.01a
• /
• pp.83-86
• /
• 2019

Histogram equalization is extensively used for image contrast enhancement in various applications due to its effectiveness and its modest functions. In image research, image enhancement is one of the most significant and arduous technique. The image enhancement aim is to improve the visual appearance of an image. Different kinds of images such as satellite images, medical images, aerial images are affected from noise and poor contrast. So it is important to remove the noise and improve the contrast of the image. Therefore, for this purpose, we apply a median filter on MR image as the median filter remove the noise and preserve the edges effectively. After applying median filter on MR image we have used intensity transformation function on the filtered image to increase the contrast of the image. Than applied the histogram equalization (HE) technique on the filtered image. The simple histogram equalization technique over enhances the brightness of the image due to which the important information can be lost. Therefore, adaptive histogram equalization (AHE) and contrast limited histogram equalization (CLAHE) techniques are used to enhance the image without losing any information.

• Journal of Audiology & Otology
• /
• v.23 no.1
• /
• pp.1-7
• /
• 2019

Self-reported difficulties in speech-in-noise (SiN) recognition are common among tinnitus patients. Whereas hearing impairment that usually co-occurs with tinnitus can explain such difficulties, recent studies suggest that tinnitus patients with normal hearing sensitivity still show decreased SiN understanding, indicating that SiN difficulties cannot be solely attributed to changes in hearing sensitivity. In fact, cognitive control, which refers to a variety of top-down processes that human beings use to complete their daily tasks, has been shown to be critical for SiN recognition, as well as the key to understand cognitive inefficiencies caused by tinnitus. In this article, we review studies investigating the association between tinnitus and cognitive control using behavioral and brain imaging assessments, as well as those examining the effect of tinnitus on SiN recognition. In addition, three factors that can affect cognitive control in tinnitus patients, including hearing sensitivity, age, and severity of tinnitus, are discussed to elucidate the association among tinnitus, cognitive control, and SiN recognition. Although a possible central or cognitive involvement has always been postulated in the observed SiN impairments in tinnitus patients, there is as yet no direct evidence to underpin this assumption, as few studies have addressed both SiN performance and cognitive control in one tinnitus cohort. Future studies should aim at incorporating SiN tests with various subjective and objective methods that evaluate cognitive performance to better understand the relationship between SiN difficulties and cognitive control in tinnitus patients.

• Journal of the Korean Society of Radiology
• /
• v.14 no.2
• /
• pp.157-168
• /
• 2020

Advancements in segmentation methodology has made automatic segmentation of brain structures using structural images accurate and consistent. One method of automatic segmentation, which involves registering atlas information from template space to subject space, requires a high quality atlas with accurate boundaries for consistent segmentation. The Allen Mouse Brain Atlas, which has been widely accepted as a high quality reference of the mouse brain, has been used in various segmentations and can provide accurate coordinates and boundaries of mouse brain structures for tractography. Through probabilistic tractography, diffusion tensor images can be used to map comprehensive neuronal network of white matter pathways of the brain. Comparisons between neural networks of mouse and human brains showed that various clinical tests on mouse models were able to simulate disease pathology of human brains, increasing the importance of clinical mouse brain studies. However, differences between brain size of human and mouse brain has made it difficult to achieve the necessary image quality for analysis and the conditions for sufficient image quality such as a long scan time makes using live samples unrealistic. In order to secure a mouse brain image with a sufficient scan time, an Ex-vivo experiment of a mouse brain was conducted for this study. Using FSL, a tool for analyzing tensor images, we proposed a semi-automated segmentation and tractography analysis pipeline of the mouse brain and applied it to various mouse models. Also, in order to determine the useful signal-to-noise ratio of the diffusion tensor image acquired for the tractography analysis, images with various excitation numbers were compared.

• Journal of Magnetics
• /
• v.17 no.2
• /
• pp.158-162
• /
• 2012

Although 3.0T magnetic resonance imaging (MRI) has the advantages of a higher signal to noise ratio (SNR) and contrast than 1.5T MRI, there are limitations on the contrast between white and grey matter because of the long T1 recovery time when T1 images are obtained using the Spin Echo Technique. To overcome this, T1 weighted images are obtained occasionally using the inversion recovery (IR) technique, which employs a relatively long TR. The aim of this study was to determine the optimal TI in a brain examination when a T1 weighted image is obtained using the IR technique. Eight participants (male: 7, female: 1, average age: $34{\pm}14.11$) with a normal diagnosis were targeted from February 18, 2012 to February 27, 2012, and the contrast between white and grey matter as well as the contrast to noise ratio (CNRs) in each participant were measured. The CNRs of white matter and grey matter were highest at TI = 600, 650, 750, 900, 1050 and 1100 ms when the TR was 1100, 1400, 1700, 2000, 2300 and 2600 ms, respectively. Therefore, as the TIs were $44.425{\pm}0.877%$ of the TRs in the TR range of 1400-2300 ms, the optimal T1 weighted images that describe the contrast between white and grey matter can be obtained if the TIs are compensated for with $44.425{\pm}0.877%$ of the TRs in the time of setting TIs.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.5
• /
• pp.442-450
• /
• 2002

In measuring EEG, which is widely used for studying brain function, EEG is frequently mixed with noise and artifact. In this study, the signals relevant to the artifact were distracted by applying ICA to EEG signal. First, each independent component which was assumed to be the source was separated by applying ICA to EEG which involved artifact relevant to the eye movement of a normal person. Next, the signal which was assumed to be artifact was removed from the separated 18 independent components, and the nonlinear analysis method such as correlation dimension and the Iyapunov exponent was applied to each reconstructed EEG signal and the original signal including artifact in order to find meaningful difference between the two signals and infer the anatomical localization of its source and distribution. This study shows it is possible not only to analyze the brain function visually and spatially for visually complex EEG signal, but also to observe its meaningful change through the quantitative analysis of EEG by means of the nonlinear analysis.

• Journal of Biomedical Engineering Research
• /
• v.45 no.2
• /
• pp.101-107
• /
• 2024

Steady-state visual evoked potential-based brain-computer interface (SSVEP-BCI) is one of the promising systems that can serve as an alternative input device due to its stable and fast performance. However, one of the major bottlenecks is that some individuals exhibit no or very low SSVEP responses to flickering stimulation, known as SSVEP illiteracy, resulting in low performance on SSVEP-BCIs. However, a lengthy duration is required to enhance multiple SSVEP responses using traditional single-frequency transcranial alternating current stimulation (tACS). This research proposes a novel approach using dual-frequency tACS (df-tACS) to potentially enhance SSVEP by targeting the two frequencies with the lowest signal-to-noise ratio (SNR) for each participant. Seven participants (five males, average age: 24.42) were exposed to flickering checkerboard stimuli at six frequencies to determine the weakest SNR frequencies. These frequencies were then simultaneously stimulated using df-tACS for 20 minutes, and the experiment was repeated to evaluate changes in SSVEP responses. The results showed that df-tACS effectively enhances the SNR at each targeted frequency, suggesting it can selectively improve target frequency responses. The study supports df-tACS as a more efficient solution for SSVEP illiteracy, proposing further exploration into multi-frequency tACS that could stimulate more than two frequencies, thereby expanding the potential of SSVEP-BCIs.

• Journal of the Ergonomics Society of Korea
• /
• v.33 no.1
• /
• pp.39-48
• /
• 2014

Objective: This entire study has two parts. Study I aimed to develop a psychological assessment scale and the study II aimed to investigate the effects of LFN (low frequency noise) on the psychological responses in humans, using the scale developed in the study I. Background: LFN is known to have a negative impact on the functioning of humans. The negative impact of LFN can be categorized into two major areas of functioning of humans, physiological and psychological areas of functioning. The physiological impact can cause abnormalities in threshold, balancing and/or vestibular system, cardiovascular system and, hormone changes. Psychological functioning includes cognition, communication, mental health, and annoyance. Method: 182 college students participated in the study I in development of a psychological assessment scale and 42 paid volunteers participated in the study II to measure psychological responses. The LFN stimuli consisted of 12 different pure tones and 12 different 1 octave-band white noises and each stimulus had 4 different frequencies and 3 different sounds pressure levels. Results: We developed the psychological assessment scale consisting of 17 items with 3 dimensions of psychological responses (i.e., perceived physical, perceived physiological, and emotional responses). The main findings of LFN on the responses were as follows: 1. Perceived psychological responses showed a linear relation with SPL (sound pressure level), that is the higher the SPL is, the higher the negative psychological responses were. 2. Psychological responses showed quadric relations with SPL in general. 3. More negative responses at 31.5Hz LFN than those of 63 and 125Hz were reported, which is deemed to be caused by perceived vibration by 31.5Hz. 'Perceived vibration' at 31.5Hz than those of other frequencies of LFN is deemed to have amplified the negative psychological response. Consequently there found different effects of low frequency noise with different frequencies and intensity (SPL) on multiple psychological responses. Conclusion: Three dimensions of psychological responses drawn in regard to this study differed from others in the frequencies and SLP of LFN. Negative psychological responses are deemed to be differently affected by the frequency, SPL of the LFN and 'feel vibration' induced by the LFN. Application: The psychological scale from our study can be applied in quantitative psychological measurement of LFN at home or industrial environment. In addition, it can also help design systems to block LFN to provide optimal conditions if used the study outcome, .i.e., the relations between physical and psychological responses of LFN.

• Progress in Superconductivity
• /
• v.4 no.2
• /
• pp.114-120
• /
• 2003

We employed a method eliminating a temporally partial principal component (PC) of multichannel-recorded neuromagnetic fields for excluding spatially correlated noises from event-evoked signals. The noises in magnetoencephalography (MEG) are considered to be mainly spontaneous neuromagnetic fields which are spatially correlated. In conventional MEG experiments, the amplitude of the spontaneous neuromagnetic field is much lager than that of the evoked signal and the synchronized characteristics of the correlated rhythmic noise makes it possible for us to extract the correlation noises from the evoked signal by means of the general PC analysis. However, the whole-time PC of the fields still contains a little projection component of the evoked signal and the elimination of the PC results in the distortion of the evoked signal. Especially, the distortion will not be negligible when the amplitude of the evoked signal is relatively large or when the evoked signals have a spatially-asymmetrical distribution which does not cancel out the corresponding elements of the covariance matrix. In the period of prestimulus, there are only the spontaneous fields and we can find the pure noise PC that is not including the evoked signal. Besides that, we propose a method, called the extended temporal decorrelation method (ETDM), to suppress the distortion of the noise PC from remanent evoked signal components. In this study, we applied the Partial Principal component elimination method (PPCE) and ETDM to simulated signals and the auditory evoked signals that had been obtained with our homemade 37-channel magnetometer-based SQUID system. We demonstrate here that PPCE and ETDM reduce the number of epochs required in averaging to about half of that required in conventional averaging.

• Progress in Superconductivity
• /
• v.5 no.2
• /
• pp.98-104
• /
• 2004

We analyzed a noise-sensitivity profile of a specific SQUID sensor system for the localization of brain activity. The location of a neuromagnetic current source is estimated from the recording of spatially distributed SQUID sensors. According to the specific arrangement of the sensors, each site in the source space has different sensitivity, that is, the difference in the lead field vectors. Conversely, channel noises on each sensor will give a different amount of the estimation error to each of the source sites. e.g., a distant source site from the sensor system has a small lead-field vector in magnitude and low sensitivity. However, when we solve the inverse problem from the recorded sensor data, we use the inverse of the lead-field vector that is rather large, which results in an overestimated noise power on the site. Especially, the spatial sensitivity profile of a gradiometer system measuring tangential fields is much more complex than a radial magnetometer system. This is one of the causes to make the solutions of inverse problems unstable on intervening of the sensor noise. In this study, in order to improve the localization accuracy, we calculated the noise-sensitivity profile of our 40-channel planar SQUID gradiometer system, and applied it as a normalization weight factor to the source localization using synthetic aperture magnetometry.

• Journal of the Korean Society of Radiology
• /
• v.5 no.6
• /
• pp.401-407
• /
• 2011

The purpose of this study is to know the differences of MR spectra, obtained from normal volunteers by variable TE value, through the quantitative analysis of brain metabolites by peak integral and SNR between 1.5T and 3.0T, together with PRESS and STEAM pulse sequence. Single-voxel MR proton spectra of the human brain obtained from normal volunteers at both 3.0T MR system (Magnetom Trio, SIEMENS, Germany) and 1.5T MR system (Signa Twinspeed, GE, USA) using the STEAM and PRESS pulse sequence. 10 healthy volunteers (3.0T:3 males, 2 females; 1.5T : 3 males, 2 females) with the range from 22 to 30 years old (mean 26 years) participated in our study. They had no personal or familial history of neurological diseases and had a normal neurological examination. Data acquisition parameters were closely matched between the two field strengths. Spectra were recorded in the white matter of the occipital lobe. Spectra were compared in terms of resolution and signal-to-noise ratio(SNR), and echo time(TE) were estimated at both field strengths. Imaging parameters was used for acquisition of the proton spectrum were as follow : TR 2000msec, TE 30ms, 40ms, 50ms, 60ms, 90ms, 144ms, 288ms, NA=96, VOI=$20{\times}20{\times}20mm3$. As the echo times were increased, the spectra obtained from 3.0T and 1.5T show decreased peak integral and SNR at both pulse sequence. PRESS pulse sequence shows higher SNR and signal intensity than those of STEAM. Especially, Spectra in normal volunteers at 3.0T demonstrated significantly improved overall SNR and spectral resolution compared to 1.5T(Fig1). The spectra acquired at short echo time, 3T MR system shows a twice improvement in SNR compared to 1.5T MR system(Table. 1). But, there was no significant difference between 3.0Tand 1.5T at long TE It is concluded that PRESS and short TE is useful for quantification of the brain metabolites at 3.0T MRS, our standardized protocol for quantification of the brain metabolites at 3.0T MRS is useful to evaluate the brain diseases by monitoring the systematic changes of biochemical metabolites concentration in vivo.