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Clinical Applications of Neuroimaging with Susceptibility Weighted Imaging: Review Article (SWI의 신경영상분야의 임상적 이용)

  • Roh, Keuntak;Kang, Hyunkoo;Kim, Injoong
    • Investigative Magnetic Resonance Imaging
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    • v.18 no.4
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    • pp.290-302
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    • 2014
  • Purpose : Susceptibility-weighted magnetic resonance (MR) sequence is three-dimensional (3D), spoiled gradient-echo pulse sequences that provide a high sensitivity for the detection of blood degradation products, calcifications, and iron deposits. This pictorial review is aimed at illustrating and discussing its main clinical applications. Materials and Methods: SWI is based on high-resolution, 3D, fully velocity-compensated gradient-echo sequences using both magnitude and phase images. To enhance the visibility of the venous structures, the magnitude images are multiplied with a phase mask generated from the filtered phase data, which are displayed at best after post-processing of the 3D dataset with the minimal intensity projection algorithm. A total of 200 patients underwent MR examinations that included SWI on a 3 tesla MR imager were enrolled. Results: SWI is very useful in detecting multiple brain disorders. Among the 200 patients, 80 showed developmental venous anomaly, 22 showed cavernous malformation, 12 showed calcifications in various conditions, 21 showed cerebrovascular accident with susceptibility vessel sign or microbleeds, 52 showed brain tumors, 2 showed diffuse axonal injury, 3 showed arteriovenous malformation, 5 showed dural arteriovenous fistula, 1 showed moyamoya disease, and 2 showed Parkinson's disease. Conclusion: SWI is useful in detecting occult low flow vascular lesions, calcification and microbleed and characterising diverse brain disorders.

Dosimetric Comparison of Three-Dimensional Conformal, Intensity-Modulated Radiotherapy, Volumetric Modulated Arc Therapy, and Dynamic Conformal Arc Therapy Techniques in Prophylactic Cranial Irradiation

  • Ismail Faruk Durmus;Dursun Esitmez;Guner Ipek Arslan;Ayse Okumus
    • Progress in Medical Physics
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    • v.34 no.4
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    • pp.41-47
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    • 2023
  • Purpose: This study aimed to dosimetrically compare the technique of three-dimensional conformal radiotherapy (3D CRT), which is a traditional prophylactic cranial irradiation method, and the intensity-modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) techniques used in the last few decades with the dynamic conformal arc therapy (DCAT) technique. Methods: The 3D CRT, VMAT, IMRT, and DCAT plans were prepared with 25 Gy in 10 fractions in a Monaco planning system. The target volume and the critical organ doses were compared. A comparison of the body V2, V5, and V10 doses, monitor unit (MU), and beam on-time values was also performed. Results: In planned target volume of the brain (PTVBrain), the highest D99 dose value (P<0.001) and the most homogeneous (P=0.049) dose distribution according to the heterogeneity index were obtained using the VMAT technique. In contrast, the lowest values were obtained using the 3D CRT technique in the body V2, V5, and V10 doses. The MU values were the lowest when DCAT (P=0.001) was used. These values were 0.34% (P=0.256) lower with the 3D CRT technique, 66% (P=0.001) lower with IMRT, and 72% (P=0.001) lower with VMAT. The beam on-time values were the lowest with the 3D CRT planning (P<0.001), 3.8% (P=0.008) lower than DCAT, 65% (P=0.001) lower than VMAT planning, and 76% (P=0.001) lower than IMRT planning. Conclusions: Without sacrificing the homogeneous dose distribution and the critical organ doses in IMRTs, three to four times less treatment time, less low-dose volume, less leakage radiation, and less radiation scattering could be achieved when the DCAT technique is used similar to conventional methods. In short, DCAT, which is applicable in small target volumes, can also be successfully planned in large target volumes, such as the whole-brain.

Optimal EEG Feature Extraction using DWT for Classification of Imagination of Hands Movement

  • Chum, Pharino;Park, Seung-Min;Ko, Kwang-Eun;Sim, Kwee-Bo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.6
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    • pp.786-791
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    • 2011
  • An optimal feature selection and extraction procedure is an important task that significantly affects the success of brain activity analysis in brain-computer interface (BCI) research area. In this paper, a novel method for extracting the optimal feature from electroencephalogram (EEG) signal is proposed. At first, a student's-t-statistic method is used to normalize and to minimize statistical error between EEG measurements. And, 2D time-frequency data set from the raw EEG signal was extracted using discrete wavelet transform (DWT) as a raw feature, standard deviations and mean of 2D time-frequency matrix were extracted as a optimal EEG feature vector along with other basis feature of sub-band signals. In the experiment, data set 1 of BCI competition IV are used and classification using SVM to prove strength of our new method.

Neuronal Spike Train Decoding Methods for the Brain-Machine Interface Using Nonlinear Mapping (비선형매핑 기반 뇌-기계 인터페이스를 위한 신경신호 spike train 디코딩 방법)

  • Kim, Kyunn-Hwan;Kim, Sung-Shin;Kim, Sung-June
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.54 no.7
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    • pp.468-474
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    • 2005
  • Brain-machine interface (BMI) based on neuronal spike trains is regarded as one of the most promising means to restore basic body functions of severely paralyzed patients. The spike train decoding algorithm, which extracts underlying information of neuronal signals, is essential for the BMI. Previous studies report that a linear filter is effective for this purpose and there is no noteworthy gain from the use of nonlinear mapping algorithms, in spite of the fact that neuronal encoding process is obviously nonlinear. We designed several decoding algorithms based on the linear filter, and two nonlinear mapping algorithms using multilayer perceptron (MLP) and support vector machine regression (SVR), and show that the nonlinear algorithms are superior in general. The MLP often showed unsatisfactory performance especially when it is carelessly trained. The nonlinear SVR showed the highest performance. This may be due to the superiority of the SVR in training and generalization. The advantage of using nonlinear algorithms were more profound for the cases when there are false-positive/negative errors in spike trains.

Isolated Leptomeningeal Enhancement in Anti-N-Methyl D-Aspartate Receptor Encephalitis: The Diagnostic Value of Contrast-Enhanced Fluid-Attenuated Inversion Recovery Imaging (항-NMDA 수용체 항체와 관련된 뇌염에서 단독 연수막 조영증강: 조영증강 유체감쇠반전회복기법 영상의 진단적 가치)

  • Jun Kyeong Park;Eun Ja Lee;Kwang Ki Kim
    • Journal of the Korean Society of Radiology
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    • v.83 no.4
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    • pp.945-950
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    • 2022
  • Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis is a common autoimmune encephalitis that is noted to be a severe but treatable disease entity. Patients with anti-NMDAR encephalitis often develop psychotic symptoms, including delusions, hallucinations, and paranoia, as well as memory impairment and persistent loss of attention. However, MRI findings in such patients show no abnormalities in most cases. Although typical brain abnormality features, known as T2 hyperintensities, involve the brain parenchyma and contrast enhancement at the cerebral cortex or overlying meninges, isolated leptomeningeal enhancement has been rarely reported in anti-NMDAR encephalitis. Herein, we report a patient with anti-NMDAR encephalitis who presented with isolated leptomeningeal enhancement, additionally showing the diagnostic value of contrast-enhanced fluid-attenuated inversion recovery imaging.

Automatic Image Segmention of Brain CT Image (뇌조직 CT 영상의 자동영상분할)

  • 유선국;김남현
    • Journal of Biomedical Engineering Research
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    • v.10 no.3
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    • pp.317-322
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    • 1989
  • In this paper, brain CT images are automatically segmented to reconstruct the 3-D scene from consecutive CT sections. Contextual segmentation technique was applied to overcome the partial volume artifact and statistical fluctuation phenomenon of soft tissue images. Images are hierarchically analyzed by region growing and graph editing techniques. Segmented regions are discriptively decided to the final organs by using the semantic informations.

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A Study on Technology Trend of Brain-Machine Interface relating to 3P Information Analysis (뇌-기계 인터페이스(BMI)에 대한 3P 정보분석)

  • Lee, Jeong-gu
    • Proceedings of the Korea Contents Association Conference
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    • 2017.05a
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    • pp.477-478
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    • 2017
  • 4차 산업혁명 시대가 도래해 인간 뇌와 기계 간 인터페이스 기술 개발이 한창이다. BMI(Brain-Machine Interface)는 뇌의 신경계로부터 신호를 측정하고 분석해 기계와 같은 외부 기기에 연결해 제어함으로써 사용자의 의사나 의도대로 기기를 움직이는 인터페이스를 만드는 것이다. 뇌-기계 인터페이스 기술은 뇌질환 치료, 장애인을 위한 로봇 팔과 로봇다리 같은 인체 결합기술, 인간과 기계와의 직접적인 정신 교류의 개발을 위한 필적인 기술이다. 본 논문에서는 4차 산업혁명의 핵심기술 중 하나인 뇌 기계 인터페이스에 대한 3P 정보분석을 수행함으로써 BMI의 R&D 및 시장진입을 위한 전략을 제시하였다.

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Analysis of Diffuse Brain Injury due to Accelerations (가속도에 의한 뇌의 미만성 부상에 관한 연구)

  • Nam, D.H.;Kim, Y.E.
    • Proceedings of the KOSOMBE Conference
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    • v.1997 no.11
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    • pp.213-217
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    • 1997
  • In this study, three-dimensional inite element model was developed and analyzed or DAI using ABAQUS. To verify the developed FE model, simulated results were compared to experimental results of human cadaver by Nahum et. al. (1977). The effect of acceleration pattern and accelerating duration time or DAI was analyzed by means of maximum shear stress and pressure distribution. DAI was favored or angular acceleration rather than linear acceleration, and occured in brain stem, pons and midbrain easily as accelerating duration time was increased.

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