• 제목/요약/키워드: Brain Signal

검색결과 655건 처리시간 0.025초

Evaluation of Modified Turbo Spin Echo Technique Compared with Double Inversion Recovery Technique in Acquisition of Black Blood Brain Vessel Image

  • Choi, Kwan-Woo;Lee, Ho-Beom;Na, Sa-Ra;Son, Soon-Yong
    • Journal of Magnetics
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    • 제21권1호
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    • pp.148-152
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    • 2016
  • The main goal was to evaluate effectiveness of a modified TSE sequence compared with DIR (double inversion recovery) sequence in acquisition of fast flow brain vessel images using signal void effect. 32 healthy volunteers (10 men and 22 women; mean age of 31 years; ranging between 28-43 years) who underwent black blood DIR sequence (group A) and the modified TSE sequence (group B) were enrolled in our study. Signal to Noise Ratio (SNR) and Contrast to Noise Ratio (CNR) of the internal carotid arteries' lumen were compared in T1 and T2 weighted images for both group A and B. The images obtained from group B showed lower SNR values in internal carotid artery than the group A in both of the T1 and T2 weighted images (11.49% and 13.66% respectively). While the CNR values were higher in the group B than the group A in both of the T1 and T2 weighted images (8.69% and 7.55 % respectively). The qualitative score of all categories were not significantly different between the two groups. Furthermore approximately 49% of the total scan time was reduced from group B. Our study is to shorten the scanning time and minimize the inconveniences of the patients in acquisition of the black blood images of brain by using the signal void effect in the modified TSE technique while keeping the diagnostic value of the test.

Heterogeneous Computation on Mobile Processor for Real-time Signal Processing and Visualization of Optical Coherence Tomography Images

  • Aum, Jaehong;Kim, Ji-hyun;Dong, Sunghee;Jeong, Jichai
    • Current Optics and Photonics
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    • 제2권5호
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    • pp.453-459
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    • 2018
  • We have developed a high-performance signal-processing and image-rendering heterogeneous computation system for optical coherence tomography (OCT) on mobile processor. In this paper, we reveal it by demonstrating real-time OCT image processing using a Snapdragon 800 mobile processor, with the introduction of a heterogeneous image visualization architecture (HIVA) to accelerate the signal-processing and image-visualization procedures. HIVA has been designed to maximize the computational performances of a mobile processor by using a native language compiler, which targets mobile processor, to directly access mobile-processor computing resources and the open computing language (OpenCL) for heterogeneous computation. The developed mobile image processing platform requires only 25 ms to produce an OCT image from $512{\times}1024$ OCT data. This is 617 times faster than the naïve approach without HIVA, which requires more than 15 s. The developed platform can produce 40 OCT images per second, to facilitate real-time mobile OCT image visualization. We believe this study would facilitate the development of portable diagnostic image visualization with medical imaging modality, which requires computationally expensive procedures, using a mobile processor.

Effect of Cold Stress on Activities of Protein kinase C Subspecies in Rat Brain Regions

  • 이재란;최명언
    • 한국응용약물학회:학술대회논문집
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    • 한국응용약물학회 1994년도 춘계학술대회 and 제3회 신약개발 연구발표회
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    • pp.259-259
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    • 1994
  • Protein kinase C (PKC) participates in many cellular signal transduction. Previously we found that PKC activity of whole rat brain was altered after an exposure to cold temperature of 4 $^{\circ}C$ (Lee and Choi, Exp. Neurobiol., 2, 6, 1993). In this time PKC activity in each region of rat brain was investigated in order to know each regions is affected mostly by the stress.

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Cerebellar Schistosomiasis: A Case Report with Clinical Analysis

  • Wan, Heng;Lei, Ding;Mao, Qing
    • Parasites, Hosts and Diseases
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    • 제47권1호
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    • pp.53-56
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    • 2009
  • The authors report here a rare case of cerebellar schistosomiasis identified by pathological diagnosis, lacking extracranial involvement. The clinical symptoms included headache, dizziness, and nausea. Studies in blood were normal and no parasite eggs were detected in stool. Computed tomography of brains showed hypodense signal, and magnetic resonance imaging showed isointense signal on T1-weighted images, hyperintense signal on T2-weighted images, and intensely enhancing nodules in the right cerebellum after intravenous administration of gadolinium. A high-grade glioma was suspected, and an operation was performed. The pathologic examination of the biopsy specimen revealed schistosomal granulomas scattered within the parenchyma of the cerebellum. The definitive diagnosis was cerebellar schistosomiasis japonica. A standard use of praziquantel and corticosteroid drugs was applied, and the prognosis was good. When the pattern of imaging examinations is present as mentioned above, a diagnosis of brain schistosomiasis should be considered.

뇌경색 시기별 MR영상의 정량적 분석 (Quantitative Analysis of MR Image in Cerebral Infarction Period)

  • 박병래;하광;김학진;이석홍;전계록
    • 대한방사선기술학회지:방사선기술과학
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    • 제23권1호
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    • pp.39-47
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    • 2000
  • In this study, we showed a comparison and analysis making use of DWI(diffusion weighted image) using early diagnosis of cerebral Infarction and with the classified T2 weighted image, FLAIR images signal intensity for brain infarction period. period of cerebral infarction after the condition of a disease by ischemic stroke. To compare 3 types of image, we performed polynomial warping and affined transform for image matching. Using proposed algorithm, calculated signal intensity difference between T2WI, DWI, FLAIR and DWI. The quantification values between hand made and calculated data are almost the same. We quantified the each period and performed pseudo color mapping by comparing signal intensity each other according to previously obtained hand made data, and compared the result of this paper according to obtained quantified data to that of doctors decision. The examined mean and standard deviation for each brain infarction stage are as follows ; the means and standard deviations of signal intensity difference between DWI and T2WI for each period are $197.7{\pm}6.9$ in hyperacute, $110.2{\pm}5.4$ in acute, and $67.8{\pm}7.2$ in subacute. And the means and standard deviations of signal intensity difference between DWI and FLAIR for each period are $199.8{\pm}7.5$ in hyperacute, $115.3{\pm}8.0$ in acute, and $70.9{\pm}5.8$ in subacute. We can quantificate and decide cerebral infarction period objectively. According to this study, DWI is very exact for early diagnosis. We classified the period of infarction occurrence to analyze the region of disease and normal region in DW, T2WI, FLAIR images.

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좌우 이두근의 근전도 출력에 따른 뇌파의 활성도 변화와 관련성 탐색 (Electroencephalogram(EEG) Activation Changes and Correlations of signal with EMG Output by left and right biceps)

  • 전부일;김종원
    • 전기전자학회논문지
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    • 제23권2호
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    • pp.727-734
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    • 2019
  • 본 논문은 인간의 의지가 뇌로부터 전달되는 과정에서 근육의 움직임이나 동작이 뇌의 특정 부위에서 유의미한 특징을 나타내는 신호를 찾아낼 수 있는지를 확인한다. 일반적으로 뇌파의 발생은 특정한 동작을 유발하고 유발된 동작으로부터 신호를 받아 변화를 보인다. 이러한 신호는 불확실성이 높으며 육안으로 판별하기엔 그 차이를 파악하기 어렵다. 따라서 분류에 앞서 어떤 신호를 분석할 것인지 정의하는 과정이 필요하다. 뇌파 혹은 뇌전도의 형태는 주파수 대역별로 분류하였을 경우, 알파, 베타, 델타, 쎄타, 감마의 영역으로 나눌 수가 있다. 뇌파의 측정 부위에 따라 활성화되는 주파수의 대역이나 에너지의 차이가 다르기 때문에 이들 신호의 특정한 크기가 정확한 동작이나 의지를 표현한다고 할 수는 없지만, 특정한 영역에서 다른 동작을 했을 경우의 뇌파 활성도를 기준으로 동작을 분류하거나, 동작에 영향을 미치는 뇌파의 경향성을 판단할 수 있다. 따라서 본 논문에서는 1차적으로 근육의 좌우 이두근의 근전도가 활성화 되는 시점을 기준으로 뇌파의 발현형태를 관찰하고, 이후 좌완과 우완의 근육 활성화에 따른 뇌파의 유의미한 차이를 뇌파를 통해 유추할 수 있는지를 검증한다. 근전도의 좌우활성화에 따른 뇌파의 분류기준을 찾을 수 있다면, 뇌로부터 발현된 신호가 각각의 근육에 전달되는 과정에서 전이된 신호의 형태를 파악하는데 도움을 줄 수 있으며, 향후 더욱 복잡한 뇌신호의 발생 유형을 통해 알려지지 않은 많은 뇌파의 정보를 활용할 수 있을 것으로 판단한다.

Enhancing Medical Images by New Fuzzy Membership Function Median Based Noise Detection and Filtering Technique

  • Elaiyaraja, G.;Kumaratharan, N.
    • Journal of Electrical Engineering and Technology
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    • 제10권5호
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    • pp.2197-2204
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    • 2015
  • In recent years, medical image diagnosis has growing significant momentous in the medicinal field. Brain and lung image of patient are distorted with salt and pepper noise is caused by moving the head and chest during scanning process of patients. Reconstruction of these images is a most significant field of diagnostic evaluation and is produced clearly through techniques such as linear or non-linear filtering. However, restored images are produced with smaller amount of noise reduction in the presence of huge magnitude of salt and pepper noises. To eliminate the high density of salt and pepper noises from the reproduction of images, a new efficient fuzzy based median filtering algorithm with a moderate elapsed time is proposed in this paper. Reproduction image results show enhanced performance for the proposed algorithm over other available noise reduction filtering techniques in terms of peak signal -to -noise ratio (PSNR), mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), image enhancement factor (IMF) and structural similarity (SSIM) value when tested on different medical images like magnetic resonance imaging (MRI) and computer tomography (CT) scan brain image and CT scan lung image. The introduced algorithm is switching filter that recognize the noise pixels and then corrects them by using median filter with fuzzy two-sided π- membership function for extracting the local information.

Making Thoughts Real - a Machine Learning Approach for Brain-Computer Interface Systems

  • Tengis Tserendondog;Uurstaikh Luvsansambuu;Munkhbayar Bat-Erdende;Batmunkh Amar
    • International Journal of Internet, Broadcasting and Communication
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    • 제15권2호
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    • pp.124-132
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    • 2023
  • In this paper, we present a simple classification model based on statistical features and demonstrate the successful implementation of a brain-computer interface (BCI) based light on/off control system. This research shows study and development of light on/off control system based on BCI technology, which allows the users to control switching a lamp using electroencephalogram (EEG) signals. The logistic regression algorithm is used for classification of the EEG signal to convert it into light on, light off control commands. Training data were collected using 14-channel BCI system which records the brain signals of participants watching a screen with flickering lights and saves the data into .csv file for future analysis. After extracting a number of features from the data and performing classification using logistic regression, we created commands to switch on a physical lamp and tested it in a real environment. Logistic regression allowed us to quite accurately classify the EEG signals based on the user's mental state and we were able to classify the EEG signals with 82.5% accuracy, producing reliable commands for turning on and off the light.

Quinic Acid Alleviates Behavior Impairment by Reducing Neuroinflammation and MAPK Activation in LPS-Treated Mice

  • Yongun Park;Yunn Me Me Paing;Namki Cho;Changyoun Kim;Jiho Yoo;Ji Woong Choi;Sung Hoon Lee
    • Biomolecules & Therapeutics
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    • 제32권3호
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    • pp.309-318
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    • 2024
  • Compared to other organs, the brain has limited antioxidant defenses. In particular, the hippocampus is the central region for learning and memory and is highly susceptible to oxidative stress. Glial cells are the most abundant cells in the brain, and sustained glial cell activation is critical to the neuroinflammation that aggravates neuropathology and neurotoxicity. Therefore, regulating glial cell activation is a promising neurotherapeutic treatment. Quinic acid (QA) and its derivatives possess anti-oxidant and anti-inflammatory properties. Although previous studies have evidenced QA's benefit on the brain, in vivo and in vitro analyses of its anti-oxidant and anti-inflammatory properties in glial cells have yet to be established. This study investigated QA's rescue effect in lipopolysaccharide (LPS)-induced behavior impairment. Orally administering QA restored social impairment and LPS-induced spatial and fear memory. In addition, QA inhibited proinflammatory mediator, oxidative stress marker, and mitogen-activated protein kinase (MAPK) activation in the LPS-injected hippocampus. QA inhibited nitrite release and extracellular signal-regulated kinase (ERK) phosphorylation in LPS-stimulated astrocytes. Collectively, QA restored impaired neuroinflammation-induced behavior by regulating proinflammatory mediator and ERK activation in astrocytes, demonstrating its potential as a therapeutic agent for neuroinflammation-induced brain disease treatments.

AR 모델을 이용한 뇌파신호의 스펙트럼 추정 (Spectral Estimation of EEG signal by AR Model)

  • 류동기;김택수;허재만;유선국;박상희
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1990년도 추계학술대회
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    • pp.114-117
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    • 1990
  • EEG signal is analyzed by two methods, analysis by visual inspection of EEG recording sheets and analysis by quantative method. Generally visual inspection method is used in the clinical field. But this method has its limitation because EEG signal is random signal. Therefore it is necessary to analyze EEG signals quantatively to obtain more precise and objective information of neural and brain. In this paper, power spectrum of EEG signal was estimated by AR(AutoRegressive) model in the frequency domain. This process is useful as a preprocessing stage for tomographic brain mapping (TBM) at each frequency, band. As a method for estimating power spectral density of EEG signals, periodogram method, autocorrelation method. covariance method, modified covariance method, and Burg method are tested in this paper.

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