• Annual Conference on Human and Language Technology
• /
• 2000.10d
• /
• pp.405-410
• /
• 2000

본 연구에서는 기능적 자기공명영상을 이용하여 한글 문장의 의미와 통사 처리에 관한 뇌의 활성화 양상을 비교함으로써 한글문장 이해의 과정에 대한 신경해부학적 증거를 찾고자 하였다. 6명의 자원자를 대상으로 문장진위판단과제를 이용하여 활성화를 유도하였다. 1.5T 초전도 자기공명영상 장치에서 EPI로 BOLD 기법을 이용하여 기능적 영상을 얻었으며 영상 후 처리는 SPM99 분석 프로그램을 이용하였다. 의미관련 통사관련 문장 모두에서 좌 우 전두회(frontal gyrus) 영역에서 활성화되었다. 의미와 통사처리 영역을 구분하기 위하여 감산법을 적용한 결과, 의미처리는 좌반구의 중측두회(middle temporal gyrus) 영역에서, 통사처리는 우반구의 하전두회(BA44) 부위에서 더 많이 활성화되었다. 의미처리에서 더 우세한 성향을 띠는 부위로 밝혀진 중측두회 영역은 의미처리시에 활성화되는 영역으로 보고하는 기존의 연구와 일치하는 결과이다. 의미와 통사 문장처리시의 뇌 활성화 양상은 뇌의 여러 영역에서 중첩되어 있기는 하지만, 특정영역에서의 차이를 보이고 있으므로, 의미와 통사처리는 다른 기전(mechanism)에 의해서 일어남을 시사해 준다.

• Journal of radiological science and technology
• /
• v.39 no.3
• /
• pp.345-352
• /
• 2016

The purpose of this study was to needed basis of measure MRI CAD development for signal to noise ratio (SNR) by pulse sequence analysis from region of interest (ROI) in brain magnetic resonance imaging (MRI) contrast. We examined images of brain MRI contrast enhancement of 117 patients, from January 2005 to December 2015 in a University-affiliated hospital, Seoul, Korea. Diagnosed as one of two brain diseases such as meningioma and cysts SNR for each patient's image of brain MRI were calculated by using Image J. Differences of SNR among two brain diseases were tested by SPSS Statistics21 ANOVA test for there was statistical significance (p < 0.05). We have analysis socio-demographical variables, SNR according to sequence disease, 95% confidence according to SNR of sequence and difference in a mean of SNR. Meningioma results, with the quality of distributions in the order of T1CE, T2 and T1, FLAIR. Cysts results, with the quality of distributions in the order of T2 and T1, T1CE and FLAIR. SNR of MRI sequences of the brain would be useful to classify disease. Therefore, this study will contribute to evaluate brain diseases, and be a fundamental to enhancing the accuracy of CAD development.

• The Korean Journal of Nuclear Medicine
• /
• v.36 no.4
• /
• pp.232-243
• /
• 2002

Purpose: We studied whether brain perfusion SPECT is useful in the psychiatric disability evaluation of patients with chronic traumatic brain injury (TBI). Materials and Methods: Sixty-nine patients (M:F=58:11, age $39{\pm}14$ years) who underwent Tc-99m HMPAO brain SPECT, brain MRI and neuropsychological (NP) tests during hospitalization in psychiatric wards for the psychiatric disability evaluation were included; the severity of injury was mild in 31, moderate in 17 and severe in 21. SPECT, MRI, NP tests were peformed $6{\sim}61$ months (mean 23 months) post-injury. Diagnostic accuracy of SPECT and MRI to show hypoperfusion or abnormal signal intensity in patients with cognitive impairment represented by NP test results were compared. Results: Forty-two patients were considered to have cognitive impairment on NP tests and 27 not. Brain SPECT showed 71% sensitivity and 85% specificity, while brain MRI showed 62% sensitivity and 93% specificity (p>0.05, McNemar test). SPECT found more cortical lesions and MRI was superior in detecting white matter lesions. Sensitivity and specificity of 31 mild TBI patients were 45%, 90% for SPECT and 27%, 100% for MRI (p>0.05, McNemar test). Among 41 patients with normal brain MRI, SPECT showed 63% sensitivity (50% for mild TBI) and 88% specificity (85% for malingerers). Conclusion: Brain SPECT has a supplementary role to neuropsychological tests in the psychiatric disability evaluation of chronic TBI patients by detecting more cortical lesions than MRI.

• Journal of the Korean Society of Radiology
• /
• v.7 no.5
• /
• pp.305-311
• /
• 2013

This study involves an experiment using functional magnetic resonance imaging(fMRI) to delineate brain activation for execution functional performance. Participates to this experiment of the normal adult (man 4, woman 6) of 10 people, is not inserts the metal all closed phobia and 24.5 year-old average ages which the operating surgeon experience which are not they were. The subject for a functional MRI experiment word -color test prosecuting attorney subject rightly at magnetic pole presentation time of 30 first editions and after presenting, uses SPM 99 programs and the image realignment, after executing a standardization (nomalization), a difference which the signal burglar considers the timely order as lattice does, pixel each image will count there probably is, in order to examine rest and active crossroad dividing independence sample t-test (p<.05). Overlapped in this standard anatomic image and got a brain activation image from level of significance 95%. With functional MRI resultant execution function inside being relation, the prefrontal lobe, anterior cingulate gyrus, parietal lobe, orbitofrontal gyrus, temporal lobe, parietal lobe was activated. The execution function promotes a recovery major role from occupational therapy, understanding about the damage mechanism is important. When confirms the brain active area which accomplishes an execution function brain plasticity develops the cognitive therapeutic method which is effective increases usefully very, will be used.

• The Journal of Korean Institute of Next Generation Computing
• /
• v.15 no.5
• /
• pp.64-74
• /
• 2019

Although a non-rigid registration has high demands in clinical practice, it has a high computational complexity and it is very difficult for ensuring the accuracy and robustness of registration. This study proposes a method of applying a non-rigid registration to 3D magnetic resonance images of brain in an unsupervised learning environment by using a deep-learning network. A feature vector between two images is produced through the network by receiving both images from two different patients as inputs and it transforms the target image to match the source image by creating a displacement vector field. The network is designed based on a U-Net shape so that feature vectors that consider all global and local differences between two images can be constructed when performing the registration. As a regularization term is added to a loss function, a transformation result similar to that of a real brain movement can be obtained after the application of trilinear interpolation. This method enables a non-rigid registration with a single-pass deformation by only receiving two arbitrary images as inputs through an unsupervised learning. Therefore, it can perform faster than other non-learning-based registration methods that require iterative optimization processes. Our experiment was performed with 3D magnetic resonance images of 50 human brains, and the measurement result of the dice similarity coefficient confirmed an approximately 16% similarity improvement by using our method after the registration. It also showed a similar performance compared with the non-learning-based method, with about 10,000 times speed increase. The proposed method can be used for non-rigid registration of various kinds of medical image data.

• Proceedings of the KSMRM Conference
• /
• 2006.11a
• /
• pp.75-75
• /
• 2006

• The Korean Journal of Applied Statistics
• /
• v.29 no.6
• /
• pp.1129-1145
• /
• 2016

Functional neuro-connectivity is one of the main issues in brain science in the sense that it is closely related to neurodynamics in the brain. In the paper, we choose fMRI as a main form of response data to brain activity due to its high resolution. We review methods for analyzing functional neuro-connectivity assuming that measurements are made on physiological responses to neuron activation. This means that we deal with a state-space and measurement model, where the state-space model is assumed to represent neurodynamics. Analysis methods and their interpretation should vary subject to what was measured. We included analysis results of real fMRI data by applying a high-dimensional autoregressive model, which indicated that different neurodynamics were required for solving different types of geometric problems.

• Progress in Medical Physics
• /
• v.16 no.1
• /
• pp.32-38
• /
• 2005

Impaired processing of facial information is one of the broad ranges of cognitive deficits seen in patients with schizophrenia. The purpose of this study was to elucidate the differences in brain activities involved in the process of facial working memory between schizophrenic patients and healthy comparison subjects. Ten patients with schizophrenia were recruited along with matched healthy volunteers as a comparison group. Functional magnetic resonance imaging (fMRI) was used to assess cortical activities during the performance of a 1-back working memory paradigm using images of neutral faces as mnemonic content. The patient group performed the tasks with reduced accuracy. Group analysis revealed that left fusiform gyrus, right superior frontal gyrus, bilateral middle frontal gyri/insula, left middle temporal gyrus, precuneus and vermis of cerebellum and showed decreased cortical activities in the patient group. On the other hand, an increased level of activation in lateral prefrontal cortex and parietal lobule was observed from the patient group, all in the right hemisphere. A decreased level of activity in the left fusiform gyrus among the patient group implicates inefficient processing of facial information. An increased level of activation in prefrontal and parietal neural networks from the patient group confirms earlier findings on the impaired working memory of patients with schizophrenia.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2004.05a
• /
• pp.118-122
• /
• 2004

본 논문에서는 인체의 머리 부분을 촬영한 의료 영상에서 뇌 영역만을 분할하는 방법에 대해 제시하고자 한다. 뇌의 해부학적 구조 및 기능적 이상 부위를 파악할 경우에 영상 내에 함께 보여지는 두개골과 뇌척수액 등을 제외한 대뇌피질 영역을 분할하면 보다 효과적인 정보 분석 및 진단이 가능하게 된다. 본 시스템에서는 3단계 알고리즘을 제시한다. 첫 번째 단계에서는 영상 내에 존재하는 잡음을 제거하기 위한 필터링이고, 두 번째 단계에서는 필터링된 결과에 대한 영상분할을 수행하는 것이다 이 때 정확한 결과 도출을 위하여 사용자의 인터렉션이 들어가게 된다. 세번째 단계에서는 형태학적 방법을 이용하여 분할 결과를 보완한다. 본 연구를 위한 실험에는 자기 공명 촬영 영상(MRI: Magnetic Resonance Imaging), 단일 광전자 방출 단층 촬영영상(SPECT: Single Photon Emission Computed Tomography), 양전자 방출 단층 촬영영상(PET: Positron Emission Tomography) 등을 사용하였다. 본 시스템에서는 다양한 모달리티의 뇌 영상에서 대뇌피질 부분을 정확하게 영상 분할함으로써 뇌의 구조적 이상을 판단하기 위한 해부학적 정보 분석을 가능케 하고 있다. 뿐만 아니라 뇌 질환에 대한 정확한 진단 시뮬레이션도 가능하게 하고자 한다.

• Journal of Biomedical Engineering Research
• /
• v.20 no.2
• /
• pp.149-154
• /
• 1999

In anatomical aspects, magnetic resonance image offers more accurate information than other medical images such as X ray, ultrasonic and CT images. This paper introduces a method that segments and detects lesion for 2 dimensional axial MR brain images automatically. Image segmentation process consists of 2 stages. First stage extracts cerebrum region using thresholding and morphology. In the second stage, white matter, gray matter and cerebrospinal fluid in the cerebrum are extracted using FCM, We could improve processing time as removing uninterested region. Finally symmetry measure and anatomical Knowledge are used to detect lesion.