• Proceedings of the Korea Contents Association Conference
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• 2004.05a
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• pp.56-62
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• 2004

In the case that we do not have enough number of training patterns because of limitation such as time consuming, economic problem, and so on, we geneterate a new patterns using the brain-style Information processing algorithm, that is, supervised and unsupervised learning methods.

• Investigative Magnetic Resonance Imaging
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• v.26 no.2
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• pp.96-103
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• 2022

Purpose: The survival of organisms critically depends on avoidance responses to life-threatening stimuli. Information about dangerous situations needs to be remembered to produce defensive behavior. To investigate underlying brain regions to process information of danger, manganese-enhanced MRI (MEMRI) was used in olfactory fear-conditioned rats. Materials and Methods: Fear conditioning was conducted in male Sprague-Dawley rats. The animals received nasal injections of manganese chloride solution to monitor brain activation for olfactory information processing. Twenty-four hours after manganese injection, rats were exposed to electric foot shocks with odor cue for one hour. Control rats were exposed to the same odor cue without foot shocks. Forty-eight hours after the conditioning, rats were anesthetized and their brains were scanned with 9.4T MRI. Acquired images were processed and statistical analyses were performed using AFNI. Results: Manganese injection enhanced brain areas involved in olfactory information pathways in T1 weighted images. Rats that received foot shocks showed higher brain activation in the central nucleus of the amygdala, septum, primary motor cortex, and preoptic area. In contrast, control rats displayed greater signals in the orbital cortex and nucleus accumbens. Conclusion: Nasal delivery of manganese solution enhanced olfactory signal pathways in rats. Odor cue paired with foot shocks activated amygdala, the central brain region in fear, and related brain circuits. Use of MEMRI in fear conditioning provides a reliable monitoring technique of brain activation for fear learning.

• Journal of Multimedia Information System
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• v.8 no.2
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• pp.79-84
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• 2021

Detecting brain tumors of different sizes is a challenging task. This study aimed to identify brain tumors using detection algorithms. Most studies in this area use segmentation; however, we utilized detection owing to its advantages. Data were obtained from 64 patients and 11,200 MR images. The deep learning model used was RetinaNet, which is based on ResNet152. The model learned three different types of pre-processing images: normal, general histogram equalization, and contrast-limited adaptive histogram equalization (CLAHE). The three types of images were compared to determine the pre-processing technique that exhibits the best performance in the deep learning algorithms. During pre-processing, we converted the MR images from DICOM to JPG format. Additionally, we regulated the window level and width. The model compared the pre-processed images to determine which images showed adequate performance; CLAHE showed the best performance, with a sensitivity of 81.79%. The RetinaNet model for detecting brain tumors through deep learning algorithms demonstrated satisfactory performance in finding lesions. In future, we plan to develop a new model for improving the detection performance using well-processed data. This study lays the groundwork for future detection technologies that can help doctors find lesions more easily in clinical tasks.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.574-575
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• 2023

뇌종양은 인체에 발생하는 여러 종양 중 세 번째로 많이 나타난다. 뇌종양 환자 수는 지속해서 증가하고 있으며, 별도의 예방법이 존재하지 않아 빠른 진단 및 종양 종류에 따른 치료가 매우 중요하다. 현재 뇌종양 진료는 전문의가 전용 소프트웨어로 뇌 Magnetic Resonance Imaging(MRI) 이미지를 확대, 축소하여 자세히 살펴보면서 종양의 크기, 위치, 양성/악성 여부 등을 판단한다. 이 방식은 의사의 숙련도에 따라 진료 시간과 판독의 차이가 크고 오진 가능성이 있다. 본 논문은 뇌종양 종류별 MRI 이미지가 학습된 CNN 모델을 사용한 의사의 뇌종양 진단 시간 단축, 진단 정확도 향상을 통해 환자 치료의 효율성을 높이는 방안으로 Brain Tumor X를 제안한다.

• The Korean Journal of Physiology and Pharmacology
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• v.13 no.5
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• pp.379-383
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• 2009

Nitric oxide (NO), a diffusible gas, is produced in the central nervous system, including the spinal cord dorsal horn and the trigeminal nucleus, the first central areas processing nociceptive information from periphery. In the spinal cord, it has been demonstrated that NO acts as pronociceptive or antinociceptive mediators, apparently in a concentration-dependent manner. However, the central role of NO in the trigeminal nucleus remains uncertain in support of processing the orofacial nociception. Thus, we here investigated the central role of NO in formalin (3%)-induced orofacial pain in rats by administering membrane-permeable or -impermeable inhibitors, relating to the NO signaling pathways, into intracisternal space. The intracisternal pretreatments with the NO synthase inhibitor L-NAME, the NO-sensitive guanylate cyclase inhibitor ODQ, and the protein kinase C inhibitor GF109203X, all of which are permeable to the cell membrane, significantly reduced the formalin-induced pain, whereas the membrane-impermeable NO scavenger PTIO significantly enhanced it, compared to vehicle controls. These data suggest that an overall effect of NO production in the trigeminal nucleus is pronociceptive, but NO extracellularly diffused out of its producing neurons would have an antinociceptive action.

• The KIPS Transactions:PartB
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• v.18B no.6
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• pp.385-388
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• 2011

Patients' privacy protection is a heated issue in medical business, as medical information in digital format transmit everywhere through networks without any limitation. A current protection method for brain images is to deface from the brain image for patient's privacy. However, the defacing process often removes important brain voxels so that the defaced brain image is damaged for medical analysis. An ad-hoc method is proposed to conceal patient's identification by adding cylindrical mask, while the brain keep all important brain voxels. The proposed lossless deformation of brain image is verified not to loose any important voxels. Futhermore, the masked brain image is proved not to be recognized by others.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.679-679
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• 2022

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.11a
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• pp.183-185
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• 2009

As imaging technology develops, magnetic resonance imaging (MRI) techniques have contributed to the understanding of brain function by providing anatomical structure of the brain and functional imaging related to information processing. Manganese-enhanced MRI (MEMRI) techniques can provide useful information about functions of the nervous system. However, systematic studies regarding information processing of pain have not been conducted. The purpose of this study was to detect brain activation during painful electrical stimulation using MEMRI with high spatial resolution. Male Sprague-Dawley rats (250-300 g) were divided into 3 groups: normal control, sham stimulation, and electric stimulation. Rats were anesthetized with 2.5% isoflurane for surgery. Polyethylene catheter (PE-10) was placed in the external carotid artery to administrate mannitol and MnCl2. The blood brain barrier (BBB) was broken by 20% D-mannitol under anesthesia mixed with urethane and a-chloralose. The hind limb was electrically stimulated with a 2Hz (10V) frequency while MnCl2 was infused. Brain activation induced by electrical stimulation was detected using a 4.7 T MRI. Remarkable signal enhancement was observed in the primary sensory that corresponds to sensory tactile stimulation at the hind limb region. These results suggest that signal enhancement is related to functional activation following electrical stimulation of the peripheral receptive field.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.496-498
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• 2023

Brain tumor segmentation problem has challenges in the tumor diversity of location, imbalance, and morphology. Attention mechanisms have recently been used widely to tackle medical segmentation problems efficiently by focusing on essential regions. In contrast, the fusion approaches enhance performance by merging mutual benefits from many models. In this study, we proposed a 3D dual fusion attention network to combine the advantages of fusion approaches and attention mechanisms by residual self-attention and local blocks. Compared to fusion approaches and related works, our proposed method has shown promising results on the BraTS 2018 dataset.

• Sleep Medicine and Psychophysiology
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• v.4 no.1
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• pp.15-28
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• 1997

Longterm memory is encoded in the neuronal connectivities of the brain. The most successful models of human memory in their operations are models of distributed and self-organized associative memory, which are founded in the principle of simulaneous convergence in network formation. Memory is not perceived as the qualities inherent in physical objects or events, but as a set of relations previously established in a neural net by simultaneousy occuring experiences. When it is easy to find correlations with existing neural networks through analysis of network structures, memory is automatically encoded in cerebral cortex. However, in the emergence of informations which are complicated to classify and correlated with existing networks, and conflictual with other networks, those informations are sent to the subcortex including hippocampus. Memory is stored in the form of templates distributed across several different cortical regions. The hippocampus provides detailed maps for the conjoint binding and calling up of widely distributed informations. Knowledge about the distribution of correlated networks can transform the existing networks into new one. Then, hippocampus consolidats new formed network. Amygdala may enable the emotions to influence the information processing and memory as well as providing the visceral informations to them. Cortico-striatal-pallido-thalamo-cortical loop also play an important role in memory function with analysis of language and concept. In case of difficulty in processing in spite of parallel process of informations, frontal lobe organizes theses complicated informations of network analysis through temporal processing. With understanding of brain mechanism of memory and information processing, the brain mechanism of mental phenomena including psychopathology can be better explained in terms of neurobiology and meuropsychology.