• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.16 no.1
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• pp.26-32
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• 2005

Neuroimaging in neurodevelopment is a fast growing area and new imaging techniques are rapidly developed every year. In the neurodevelopmental viewpoint, the definitive psychopathology in child and adolescent psychiatric disorders are not yet known. But many consistent findings in neuroimaging studies are being published recently. This review describes the past, present, future and limitation of neuroimaging study in neurodevelopmental perspectives.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.53-62
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• 2007

In this paper, it can propose that Fuzzy Wavelet Morphology Neural Networks for the edge detection algorithm with being robustly a unclear boundary parts by brightness difference and being less sensitivity on direction to be detected the edges of images. This is applying the Fuzzy Wavelet Morphology Operator which can be simple the image robustly without the loss of data to DTCNN Structure for improving defect which carrys out a lot of operation complexly. Also, this color image can segment Y image with YCbCr space color model which has a lossless feature information of edge boundary sides effectively. This paper can offer the simulation of color images of 50ea for the performance verification of the proposal algorithm.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.234-242
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• 2024

We propose a passive sonar signal classification algorithm using Graph Neural Network (GNN). The proposed algorithm segments spectrograms into image patches and represents graphs through connections between adjacent image patches. Subsequently, Graph Convolutional Network (GCN) is trained using the represented graphs to classify signals. In experiments with publicly available underwater acoustic data, the proposed algorithm represents the line frequency features of spectrograms in graph form, achieving an impressive classification accuracy of 92.50 %. This result demonstrates a 8.15 % higher classification accuracy compared to conventional Convolutional Neural Network (CNN).

• Journal of Neurocritical Care
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• v.11 no.2
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• pp.148-151
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• 2018

• The Journal of the Acoustical Society of Korea
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• v.37 no.2
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• pp.118-128
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• 2018

In this paper, we have studied how to search an underwater object by learning the image generated by the side scan sonar in the convolution neural network. In the method of human side analysis of the side scan image or the image, the convolution neural network algorithm can enhance the efficiency of the analysis. The image data of the side scan sonar used in the experiment is the public data of NSWC (Naval Surface Warfare Center) and consists of four kinds of synthetic underwater objects. The convolutional neural network algorithm is based on Faster R-CNN (Region based Convolutional Neural Networks) learning based on region of interest and the details of the neural network are self-organized to fit the data we have. The results of the study were compared with a precision-recall curve, and we investigated the applicability of underwater object detection in convolution neural networks by examining the effect of change of region of interest assigned to sonar image data on detection performance.

• Korean Journal of Biological Psychiatry
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• v.8 no.1
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• pp.71-78
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• 2001

The current understanding of the neurobiology of anxiety is generally based on experimental animal model, empirical effective psychopharmacological agents, chemical and naturalistic challenge paradigms, and psychoendocinological assessment. This article focuses on reviewing neuroanantomical, neuroendocinological and neurofunctional research of anxiety disorder. In the decade ahead, we anticipate that extension of current research and the new integrated approach promise novel insight into mechanism of anxiety.

• The Journal of the Korean bone and joint tumor society
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• v.9 no.2
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• pp.212-216
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• 2003

A Common peroneal nerve palsy caused by ganglionic cyst is very rare condition but well recognised entities. There have been three previous reports describing the magnetic resonance image (MRI) findings of peroneal nerve entrapment due to a ganglionic cyst. Ultrasonography, MRI, and electromyography (EMG), nerve conduction velocity (NCV), and microscopic examination were taken for diagnosis. A tubular structure near the fibular neck extending longitudinally over several slices with an inferior extension towards the superior tibiofibular joint with high T2 signal intensity was characteristic. The peroneal nerve was exposed and the ganglionic cyst was excised. The nerve was paralysed immediately after operation, but at 4 month after operation, started recovery of the function gradually and has recovered completely at 7 month. MRI is helpful to detect the extent, location, and origin of the cyst. Meticulous surgical excision can provide favorable result.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1
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• pp.13-21
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• 1995

In this paper, we improve an image classifier algorithm based on neural network learning. It consists of two steps. The first is input pattern generation and the second, the global neural network implementation using an improved back-propagation algorithm. The feature vector for pattern recognition consists of the codebook data obtained from self-organization feature map learning. It decreases the input neuron number as well as the computational cost. The global neural network algorithm which is used in classifier inserts a control part and an address memory part to the back-propagation algorithm to control weights and unit-offsets. The simulation results show that it does not fall into the local minima and can implement easily the large-scale neural network. And it decreases largely the learning time.

• The Journal of Korean Orthopaedic Ultrasound Society
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• v.1 no.1
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• pp.64-72
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• 2008

Compression neuropathy around elbow and wrist are one of the common disturbing problems in the upper extremity. The understanding of normal nerve architectures and pathophysiologic changes in compression neuropathy is important to interpret the ultrasonographic images correctly. Compression neuropathies have characteristic ultrasonographic imaging features of flattened nerve at compression and hypoechoic swollen nerve with loss of fascicular patterns at proximal segments. Dynamic ultrasonographic imagings on motion can show dymanic subluxation of ulnar nerve and medial head of triceps muscle over the medial epicondyle in snapping triceps syndrome. Dynamic compression of median nerve also can be visualized in pronator teres syndrome by dynamic imaging studies. A quantitative measures of cross sectional area or compression ratio can be helpful to diagnose compression neuropathies, such as carpal tunnel syndrome or cubital tunnel syndrome. With the clinical features and electeophysiologic studies, the untrasonographic imagings are useful tool for evaluation of the compression neuropathies in the upper extremities.

• Therapeutic Science for Rehabilitation
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• v.2 no.1
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• pp.5-12
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• 2013

The purpose of this review is to address the flow of current neuroscientific researches and to provide for the clinicians with therapeutic evidences for schizophrenia which can help them clinical decision making. Since the very beginning, a lot of scientific studies about schizophrenia have been undertaken. In this review, I describes the evidences focused on development of schizophrenia including neurobiological dysfunction, neurodevelopmental model, Kalirin, and Brain-Derived Neurotrophic Factor(BDNF) and neuroanatomic abnormalities based on neuroimaging studies. In conclusion, schizophrenia influencing on broad impairment of human function such as activities of daily life, occupations, and relationships has been studied underlying causes and treatments, but still remained uncertainty. However, there are plenty of useful evidences available for the clinicians to make a good therapeutic choice.