• Childhood Kidney Diseases
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• v.5 no.1
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• pp.22-29
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• 2001

Purpose : 99mTc DMSA renal scan have been widely used not only for tile evaluation of renal scars but also for the diagnosis of acute pyelonephritis. Recent studies have shown SPECT images have higher accuracy than the planar images with some controversy. We evaluated the availability of the SPECT images adding to planar images for the diagnosis of acute pyelonephritis(APN) and renal scar in children with urinary tract infection (UTI). Methods : 130 children with UTI (260 kidney units) and 22 follow-up children (44 kidney units) were included between January 1, 1997 and July 31, 1999 at Ewha University Mokdong Hospital. Planar Anterior and posterior images and SPECT axial and coronal images of 99mTc DMSA renal scan were obtained with Starcam 4000-i U.S.A. GE at 3 hours after 99mTc DMSA I.V. injection. The data were analyzed by Chi square test after Yates's correction. Results : The detection rate of the acute pyelonephritis by SPECT images was 12.3$\%$ higher than that of planar images ($47.7\%\;vs\;35.4\%$) by the patient and 6.9$\%$ higher also ($31.9\%\;vs\;25.4\%$) by the kidney unit. 18 kidney units with negative planar images had focal defect in 10 kidney units (3.8$\%$) and multifocal defect in 8 kidney units (3.1$\%$) on SPECT images, but 1 kidney unit with positive planar image had negative SPECT image. SPECT images were superior to tile planar images in 17.3$\%$. identical in 82.3$\%$ and inferior in 0.4$\%$ to planar image. The detection rate of tile renal scars by SPECT images was 13.7$\%$ higher than planar images by the patient ($68.2\%\;vs\;54.5\%$) and 6.8$\%$ higher also ($43.2\%\;vs\;36.4\%$) by the kidney unit. SPECT images were superior to the planar images in 17.3$\%$ and identical in 82.3$\%$ to planar image. Conclusion SPECT images had shown higher detection rate and better image than planar images for the diagnosis of the acute pyelonephritis and the evaluation of the renal scars. (J. Korean Soc Pediatr Nephrol 5 : 22- 9, 2001)

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.504-506
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• 1993

The Joint Photographic Experts Group (JPEG) standard was proposed by the International Standardization Organization (ISO/SC 29/WG 10) and the CCITT SG VIII as an international standard for digital continuous-tone still image compression. The JPEG standard has been widely accepted in electronic imaging, computer graphics, and multi-media applications, however, due to the lossy character of the JPEG compression its application in the field of medical imaging has been limited. In this paper, the JPEG standard was applied to a series of head sections of magnetic resonance (MR) images (256 gray levels, $256{\times}256$ size) and its performance was investigated. For this purpose, DCT-based sequential mode of the JPEG standard was implemented using the CL550 compression chip and progressive and lossless coding was implemented by software without additional hardware. From the experiment, it appears that the compression ratio of about 10 to 20 was obtained for the MR images without noticeable distortion. It is also noted that the error signal between the reconstructed image by the JPEG and the original image was nearly random noise without causing any special-pattern-related artifact. Although the coding efficiency of the progressive and hierarchical coding is identical to that of the sequential coding in compression ratio and SNR, it has useful features In fast search of patient Image from huge image data base and in remote diagnosis through slow public communication channel.

• Journal of the Korean Society of Radiology
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• v.17 no.2
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• pp.191-199
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• 2023

This study aimed to propose minimized radiation doses with an optimized abdomen x-ray image, which realizes a Deep Blind Image Super-Resolution Generative adversarial network (BSRGAN) technique. Entrance surface doses (ESD) measured were collected by changing exposure conditions. In the identical exposures, abdominal images were acquired and were processed with the BSRGAN. The images reconstructed by the BSRGAN were compared to a reference image with 80 kVp and 320 mA, which was evaluated by mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM). In addition, signal profile analysis was employed to validate the effect of the images reconstructed by the BSRGAN. The exposure conditions with the lowest MSE (about 0.285) were shown in 90 kVp, 125 mA and 100 kVp, 100 mA, which decreased the ESD in about 52 to 53% reduction), exhibiting PSNR = 37.694 and SSIM = 0.999. The signal intensity variations in the optimized conditions rather decreased than that of the reference image. This means that the optimized exposure conditions would obtain reasonable image quality with a substantial decrease of the radiation dose, indicating it could sufficiently reflect the concept of As Low As Reasonably Achievable (ALARA) as the principle of radiation protection.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.6
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• pp.55-64
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• 2017

High-capacity, high-definition image applications need to process considerable amounts of data at high speed. Accordingly, users of these applications demand a high-speed parallel execution system. To increase the speed of a parallel execution system, Park (2004) proposed a technique, called MAMS (Multi-Access Memory System), to access data in several execution units without the conflict of parallel processing memories. Since then, many studies on MAMS have been conducted, furthering the technique to MAMS-PP16 and MAMS-PP64, among others. As a memory architecture for parallel processing, MAMS must be constructed in one chip; therefore, a method to achieve the identical functionality as the existing MAMS while minimizing the architecture needs to be studied. This study proposes a method of miniaturizing the MAMS architecture in which the architectures of the ACR (Address Calculation and Routing) circuit and MMS (Memory Module Selection) circuit, which deliver data in memories to parallel execution units (PEs), do not use the MMS circuit, but are constructed as one shift and conditional statements whose number is the same as that of memory modules inside the ACR circuit. To verify the performance of the realized architecture, the study conducted the processing time of the proposed MAMS-PP64 through an image correlation test, the results of which demonstrated that the ratio of the image correlation from the proposed architecture was improved by 1.05 on average.

• Journal of Biomedical Engineering Research
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• v.19 no.5
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• pp.469-476
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• 1998

In the case of acquisition and displaying medical Images such as ultrasonography and endoscopy on VGA monitor of PC system, image degradation of tear-drop appears through scan conversion. In this study, we compare several methods which can solve this degradation and implement the hardware system that resolves this problem in real-time with PC. It is possible to represent high quality image display and real-time processing and acquisition with specific de-interlacing device and PCI bridge on our hardware system. Image quality is improved remarkably on our hardware system. It is implemented as PC-based system, so acquiring, saving images and describing text comment on those images and PACS networking can be easily implemented.metabolism. All images were spatially normalized to MNI standard PET template and smoothed with 16mm FWHM Gaussian kernel using SPM96. Mean count in cerebral region was normalized. The VOls for 34 cerebral regions were previously defined on the standard template and 17 different counts of mirrored regions to hemispheric midline were extracted from spatially normalized images. A three-layer feed-forward error back-propagation neural network classifier with 7 input nodes and 3 output nodes was used. The network was trained to interpret metabolic patterns and produce identical diagnoses with those of expert viewers. The performance of the neural network was optimized by testing with 5~40 nodes in hidden layer. Randomly selected 40 images from each group were used to train the network and the remainders were used to test the learned network. The optimized neural network gave a maximum agreement rate of 80.3% with expert viewers. It used 20 hidden nodes and was trained for 1508 epochs. Also, neural network gave agreement rates of 75~80% with 10 or 30 nodes in hidden layer. We conclude that artificial neural network performed as well as human experts and could be potentially useful as clinical decision support tool for the localization of epileptogenic zones.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.92-100
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• 2011

In this paper, we propose a novel blind digital watermarking method based on a cellular automata transform (CAT). CAT is based on dynamic systems known as cellular automata(CA) and uses transform bases which are differently defined by a rule number, the number of neighbors, the number of cells, and an initial state, etc. The proposed CAT based method is compared with a blind watermarking method based on DWT which is commonly used for a domain transform in signal processing. We analyse properties on changes of DWT coefficients and CAT coefficients under various attacks and determine optimal parameters for a watermarking method robust to attacks. The simulations show that the watermarked images with high PSNR and MSSIM look visually identical to originals and are robust against most of typical image processing attacks. Moreover, the proposed CAT based watermarking method is superior to the DWT based one in robustness to most of typical image processing attacks including JPEG compression, median and average filtering, scaling, cropping, and histogram equalization.

• Computers and Concrete
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• v.18 no.3
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• pp.319-336
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• 2016

In this study, both two- and three-dimensional (2D and 3D) finite-volume-based models were developed to analyze the heat transfer mechanisms through the porous structures of cellular concretes under steady-state heat transfer conditions and to investigate the differences between the 2D and 3D modeling results. The 2D and 3D reconstructed pore networks were generated from the microstructural information measured by 3D images captured by X-ray computerized tomography (X-CT). The computed effective thermal conductivities based on the 2D and 3D calculations performed on the reconstructed porous structures were found to be nearly identical to those evaluated from the 2D cross-sectional images and the 3D X-CT images, respectively. In addition, the 3D computed effective thermal conductivity was found to agree better with the measured values, in comparison with the 2D reconstruction and real cross-sectional images. Finally, the thermal conductivities computed for different reconstructed porous 3D structures of cellular concretes were compared with those obtained from 2D computations performed on 2D reconstructed structures. This comparison revealed the differences between 2D and 3D image-based modeling. A correlation was thus derived between the results of the 3D and 2D models.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.69-75
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• 2014

Existing People Counting System using a single overhead mounted camera has limitation in object recognition and counting in various environments. Those limitations are attributable to overlapping, occlusion and external factors, such as over-sized belongings and dramatic light change. Thus, this paper proposes the new concept of People Counting System by Facial Age Group using two depth cameras, at overhead and frontal viewpoints, in order to improve object recognition accuracy and robust people counting to external factors. The proposed system is counting the pedestrians by five process such as overhead image processing, frontal image processing, identical object recognition, facial age group classification and in-coming/out-going counting. The proposed system developed by C++, OpenCV and Kinect SDK, and it target group of 40 people(10 people by each age group) was setup for People Counting and Facial Age Group classification performance evaluation. The experimental results indicated approximately 98% accuracy in People Counting and 74.23% accuracy in the Facial Age Group classification.

• Journal of The Korean Astronomical Society
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• v.45 no.4
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• pp.93-99
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• 2012

We present a 1.1mm emission map of the OMC1 region observed with AzTEC, a new large-format array composed of 144 silicon-nitride micromesh bolometers, that was in use at the James Clerk Maxwell Telescope (JCMT). These AzTEC observations reveal dozens of cloud cores and a tail of filaments in a manner that is almost identical to the submillimeter continuum emission of the entire OMC1 region at 450 and $850{\mu}m$. We perform Fourier analysis of the image with a modified periodogram and the density power spectrum, which provides the distribution of the length scale of the structures, is determined. The expected value of the periodogram converges to the resulting power spectrum in the mean squared sense. The present analysis reveals that the power spectrum steepens at relatively smaller scales. At larger scales, the spectrum flattens and the power law becomes shallower. The power spectra of the 1.1mm emission show clear deviations from a single power law. We find that at least three components of power law might be fitted to the calculated power spectrum of the 1.1mm emission. The slope of the best fit power law, ${\gamma}{\approx}-2.7$ is similar to those values found in numerical simulations. The effect of beam size and the noise spectrum on the shape and slope of the power spectrum are also included in the present analysis. The slope of the power law changes significantly at higher spatial frequency as the beam size increases.