• Journal of Multimedia Information System
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• v.3 no.4
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• pp.155-160
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• 2016

The Pulse Coupled Neural Network (PCNN) is a kind of neural network models that consists of spiking neurons and local connections. The PCNN was originally proposed as a model that can reproduce the synchronous phenomena of the neurons in the cat visual cortex. Recently, the PCNN has been applied to the various image processing applications, e.g., image segmentation, edge detection, pattern recognition, and so on. The method for the image matching using the PCNN had been proposed as one of the valuable applications of the PCNN. In this method, the Genetic Algorithm is applied to the PCNN parameter learning for the image matching. In this study, we propose the method of the similar image rating using the PCNN. In our method, the Genetic Algorithm based method is applied to the parameter learning of the PCNN. We show the performance of our method by simulations. From the simulation results, we evaluate the efficiency and the general versatility of our parameter learning method.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.802-805
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• 2002

In the three-dimensional domain image expressed with two-dimensional slice images, such as fMRI images and multi-slice CT images, we propose the three-dimensional domain automatic segmentation for the purpose of extracting region. In this paper, we segmented each domain from the fMRI images of the head of people and monkey. We used the neural network "Pulse-Coupled Neural Network" which is one of the models of visual cortex of the brain based on the knowledge from neurophysiology as the technique. By using this technique, we can segment the region without any learning. Then, we reported the result of division of each domain and extraction to the fMRI slice images of human's head using "three-dimensional Pulse-Coupled Neural Network" which is arranged and created the neuron in the shape of a three-dimensional lattice.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.363-364
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• 2002

We describe quadrature type surface coil for functional magnetic resonance imaging at 3T MRI system. The coil consisted of two coplanar resonators and was used as both transmitter and receiver. The signal-to-noise ratio (SNR) of the coil was compared with that of a standard birdcage head coil. Visual cortex activation on normal subjects using LED flicker was performed. The SNR of surface coil was found to be better than that of the conventional head coil.

• The Korean Journal of Physiology and Pharmacology
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• v.16 no.6
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• pp.369-378
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• 2012

Analysis of synaptic plasticity together with behavioral and molecular studies have become a popular approach to model autism spectrum disorders in order to gain insight into the pathosphysiological mechanisms and to find therapeutic targets. Abnormalities of specific types of synaptic plasticity have been revealed in numerous genetically modified mice that have molecular construct validity to human autism spectrum disorders. Constrained by the feasibility of technique, the common regions analyzed in most studies are hippocampus and visual cortex. The relevance of the synaptic defects in these regions to the behavioral abnormalities of autistic like behaviors is still a subject of debate. Because the exact regions or circuits responsible for the core features of autistic behaviors in humans are still poorly understood, investigation using region-specific conditional mutant mice may help to provide the insight into the neuroanatomical basis of autism in the future.

• Clinical Endoscopy
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• v.55 no.5
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• pp.594-604
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• 2022

Over the past decade, technological advances in deep learning have led to the introduction of artificial intelligence (AI) in medical imaging. The most commonly used structure in image recognition is the convolutional neural network, which mimics the action of the human visual cortex. The applications of AI in gastrointestinal endoscopy are diverse. Computer-aided diagnosis has achieved remarkable outcomes with recent improvements in machine-learning techniques and advances in computer performance. Despite some hurdles, the implementation of AI-assisted clinical practice is expected to aid endoscopists in real-time decision-making. In this summary, we reviewed state-of-the-art AI in the field of gastrointestinal endoscopy and offered a practical guide for building a learning image dataset for algorithm development.

• Progress in Medical Physics
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• v.15 no.4
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• pp.228-236
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• 2004

Retinal ganglion cells transmit visual scene as an action potential to visual cortex through optic nerve. Conventional recording method using single intra- or extra-cellular electrode enables us to understand the response of specific neuron on specific time. Therefore, it is not possible to determine how the nerve impulses in the population of retinal ganglion cells collectively encode the visual stimulus with conventional recording. This requires recording the simultaneous electrical signals of many neurons. Recent advances in multi-electrode recording have brought us closer to understanding how visual information is encoded by population of retinal ganglion cells. We examined how ganglion cells act together to encode a visual scene with multi-electrode array (MEA). With light stimulation (on duration: 2 sec, off duration: 5 sec) generated on a color monitor driven by custom-made software, we isolated three functional types of ganglion cell activities; ON (35.0$\pm$4.4%), OFF (31.4$\pm$1.9%), and ON/OFF cells (34.6$\pm$5.3%) (Total number of retinal pieces = 8). We observed that nearby neurons often fire action potential near synchrony (< 1 ms). And this narrow correlation is seen among cells within a cluster which is made of 6～8 cells. As there are many more synchronized firing patterns than ganglion cells, such a distributed code might allow the retina to compress a large number of distinct visual messages into a small number of ganglion cells.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.427-434
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• 2016

This paper focuses on a real-time hardware processing by implementing the ARM Cortex-M4 based embedded system, using a conversion algorithm from a muscular sense to both visual and auditory elements, which recognizes rotations of a human body, directional changes and motion amounts out of human senses. As an input method of muscular sense, AHRS(Attitude Heading Reference System) was used to acquire roll, pitch and yaw values in real time. These three input values were converted into three elements of HSI color model such as intensity, hue and saturation, respectively. Final color signals were acquired by converting HSI into RGB color model. In addition, Three input values of muscular sense were converted into three elements of sound such as octave, scale and velocity, which were synthesized to give an output sound using MIDI(Musical Instrument Digital Interface). The analysis results of both output color and sound signals revealed that input signals of muscular sense were correctly converted into both color and sound in real time by the proposed conversion method.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.35 no.4
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• pp.362-369
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• 1990

In order to determine the mechanism of saline stress, forage plants were irrigated with sea water. Saline stress was investigated on photosynthesis, root respiration, evapotranspiration and visual symptoms. All crops showed increased relative evapotranspiration and relative photosynthesis under low temperature (11-16$^{\circ}C$) rather than high temperature (22-24$^{\circ}C$). The correlation coefficients calculated for each crop between relative evapotranspiration and root respiration were 0.996$\^$**/ for orchard grass, 0.828$\^$*/ for alfalfa and 0.963$\^$**/ for white clover. No significant correlation coefficient between relative evapotranspiration and root repiration was found for the tall fescue. The effects of OED spray on the evapotranspiration and root respiration of crops in the sea watered pots were low compared with those in the fresh watered pots. When OED was sprayed and zeolite was used, the evapotranspiration and root respiration were low compared with check pots and sand pots. The root damage due to sea water treatment was characterized by brown colored root cortex in orchard grass and tall fescue, and water penetration of root cortex in alfalfa and white clover.

• Korean Journal of Clinical Laboratory Science
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• v.47 no.1
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• pp.46-50
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• 2015

The previous studies showed that the visual imagery activated the occipital and posterior inferior temporal area of the brain, and the damage to the occipital cortex impaired the visual mental imagery. We studied current-source distribution of electroencephalography (EEG) to observe neuronal activity during imagery tennis playing. Eleven healthy volunteers were enrolled. All volunteers were right-handed males and novices for tennis playing. The mean age of them was 24.9 years. The EEGs were recorded on the scalp electrodes located according to the International 10~20 System. The number of electrodes was 25 channels including subtemporal electrodes. The EEG recording session was 13 min including 5 segments: resting-I, scenery-slide show, resting-II, watching tennis-game video, and imagery-tennis playing. The recoding durations were 3, 2, 3, 2, and 3 min respectively. Five 'artifact free 3-sec segments' were selected in each segment of 'imagery-tennis playing' and 'resting-II'. We did the frequency domain analysis with the EEG segments using a distributed model of current-source analysis. The statistical-nonparametric maps (SnPMs) were obtained between the segments of 'imagery-tennis playing' and the segments of 'resting-II' (p<0.01). The significant change of current-source density was observed only in alpha-2 frequency band (10~12 Hz). The current-sourcedensity was increased in the hippocampus, parahippocampus, and occipital fusiform gyrus in the right cerebral hemisphere (p<0.01). Imaginary-tennis playing may activate the hippocampal-occipital alpha networks of nondominant hemisphere.

• Progress in Superconductivity and Cryogenics
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• v.17 no.4
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• pp.34-37
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• 2015

Developing Magnetoencephalography (MEG) based on Superconducting Quantum Interference Device (SQUID) facilitates to observe the human brain functions in non-invasively and high temporal and high spatial resolution. By using this MEG, we studied alpha rhythm (8-13 Hz) that is one of the most predominant spontaneous rhythm in human brain. The 8-13 Hz rhythm is observed in several sensory region in the brain. In visual related region of occipital, we call to alpha rhythm, and auditory related region of temporal call to tau rhythm, sensorimotor related region of parietal call to mu rhythm. These rhythms are decreased in task related region and increased in task irrelevant regions. This means that these rhythms play a pivotal role of inhibition in task irrelevant region. It may be helpful to attention to the task. In several literature about the alpha-band inhibition in multi-sensory modality experiment, they observed this effect in the occipital and somatosensory region. In this study, we hypothesized that we can also observe the alpha-band inhibition in the auditory cortex, mediated by the tau rhythm. Before that, we first investigated the existence of the alpha and tau rhythm in occipital and temporal region, respectively. To see these rhythms, we applied the visual and auditory stimulation, in turns, suppressed in task relevant regions, respectively.