• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.3
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• pp.102-109
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• 2009

Purpose: Flash 3D (pixon(R) method; 3D OSEM) was developed as a software program to shorten exam time and improve image quality through reconstruction, it is an image processing method that usefully be applied to nuclear medicine tomography. If perfoming brain diamox perfusion scan by reconstructing subtracted images by Flash 3D with shortened image acquisition time, there was a problem that SNR of subtracted image is lower than basal image. To increase SNR of subtracted image, we use LEAP collimators, and we emphasized on sensitivity of vessel dilatation than resolution of brain vessel. In this study, our purpose is to confirm possibility of application of LEAP collimators at brain diamox perfusion tomography, identify proper reconstruction factors by using Flash 3D. Materials and methods: (1) The evaluation of phantom: We used Hoffman 3D Brain Phantom with $^{99m}Tc$. We obtained images by LEAP and LEHR collimators (diamox image) and after 6 hours (the half life of $^{99m}Tc$: 6 hours), we use obtained second image (basal image) by same method. Also, we acquired SNR and ratio of white matters/gray matters of each basal image and subtracted image. (2) The evaluation of patient's image: We quantitatively analyzed patients who were examined by LEAP collimators then was classified as a normal group and who were examined by LEHR collimators then was classified as a normal group from 2008. 05 to 2009. 01. We evaluate the results from phantom by substituting factors. We used one-day protocol and injected $^{99m}Tc$-ECD 925 MBq at both basal image acquisition and diamox image acquisition. Results: (1) The evaluation of phantom: After measuring counts from each detector, at basal image 41~46 kcount, stress image 79~90 kcount, subtraction image 40~47 kcount were detected. LEAP was about 102~113 kcount at basal image, 188~210 kcount at stress image and 94~103 at subtraction image kcount were detected. The SNR of LEHR subtraction image was decreased than LEHR basal image about 37%, the SNR of LEAP subtraction image was decreased than LEAP basal image about 17%. The ratio of gray matter versus white matter is 2.2:1 at LEHR basal image and 1.9:1 at subtraction, and at LEAP basal image was 2.4:1 and subtraction image was 2:1. (2) The evaluation of patient's image: the counts acquired by LEHR collimators are about 40~60 kcounts at basal image, and 80~100 kcount at stress image. It was proper to set FWHM as 7 mm at basal and stress image and 11mm at subtraction image. LEAP was about 80~100 kcount at basal image and 180~200 kcount at stress image. LEAP images could reduce blurring by setting FWHM as 5 mm at basal and stress images and 7 mm at subtraction image. At basal and stress image, LEHR image was superior than LEAP image. But in case of subtraction image like a phantom experiment, it showed rough image because SNR of LEHR image was decreased. On the other hand, in case of subtraction LEAP image was better than LEHR image in SNR and sensitivity. In all LEHR and LEAP collimator images, proper subset and iteration frequency was 8 times. Conclusions: We could archive more clear and high SNR subtraction image by using proper filter with LEAP collimator. In case of applying one day protocol and reconstructing by Flash 3D, we could consider application of LEAP collimator to acquire better subtraction image.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.9
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• pp.700-704
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• 2009

In this paper, we propose a method for combining MR image with histopathology image of the prostate using image correction and multi-stage registration. Our method consists of four steps. First, the intensity of prostate bleeding area on T2-weighted MR image is substituted for that on T1-weighted MR image. And two or four tissue sections of the prostate in histopathology image are combined to produce a single prostate image by manual stitching. Second, rigid registration is performed to find the affine transformations that to optimize mutual information between MR and histopathology images. Third, the result of affine registration is deformed by the TPS warping. Finally, aligned images are visualized by the intensity intermixing. Experimental results show that the prostate tumor lesion can be properly located and clearly visualized within MR images for tissue characterization comparison and that the registration error between T2-weighted MR and histopathology image was 0.0815mm.

• Korean Journal of Cognitive Science
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• v.22 no.4
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• pp.347-364
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• 2011

In this paper, we propose a automatic image bases extraction method for visual image reconstruction from brain activity using Non-negative Matrix Factorization (NMF). Image bases are basic elements to construct and present a visual image. Previous method used brain activity that evoked by predefined 361 image bases of four different sizes: $1{\times}1$, $2{\times}1$, $1{\times}2$, $2{\times}2$, and $2{\times}2$. Then the visual stimuli were reconstructed by linear combination of all the results from these image bases. While the previous method used 361 predefined image bases, the proposed method automatically extracts image bases which represent the image data efficiently. From the experiments, we found that the proposed method reconstructs the visual stimuli better than the previous method.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.2
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• pp.321-330
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• 2022

This study analyzed the difference between 2D image and 3D virtual clothing images based on stripe arrangement to obtain fundamental data for slim appearance. First, the slimming effect according to the three types of stripe ratio was examined. Subsequently, the slimming effects of seven types of one-piece dress designs according to the stripe location were analyzed. Subjective ranking was evaluated. The width items and radius of curvature were measured for the image's respective parts. Consequently, in 2D image and 3D virtual clothing images, the one with the narrowest stripe ratio was evaluated as the slimmest; however, the conditions for the slimming effect were different. In the seven one-piece dress designs, a difference was apparent in the ranking of the 2D image and 3D virtual clothing images. In the 3D virtual clothing image, arranging the stripes on the entire garment proved inefficient. The stripes were curved according to the curvature of the human body, creating an optical illusion that differed from that of the 2D image.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.526-529
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• 2007

Due to its inherent feature of high-resolution satellite, there is strong need in some specific area to minimize the processing time required to get a standard image on hand from downlink signal acquisition. However, in general image processing system, it takes considerable time to get image data up to certain level from raw data acquisition because the huge amount of data is dealt sequentially as input data. This paper introduces the high-speed image processing system which generates the image data only for the area selected by user. To achieve the high speed performance, this system includes Quick Look Image display function with sampling, ROI selection function, Image Line Index function, and Distributed processing function. The developed RPS was applied to KOMPSAT-2 320Mbps downlink channel and its effectiveness was successfully demonstrated. This feature to provide the image product very quickly is expected to promote the application of high resolution satellite image.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.10 no.2
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• pp.53-66
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• 2006

Recent technique has shown high interest in 3D stereoscopic image, one out of high immersion appearance techniques. Unlike general 2D image, 3D stereoscopic image is generated by 3D geometric information. Therefore, the lack of 3D geometric information sometimes imposes restrictions or makes editing more tedious. We propose a new unsupervised technique aimed to generate stereoscopic image which is estimated by depth-map information using image-based modeling from a single input image. The proposed system is implemented as the Adobe Photoshop(R) plug-in for considering generality and expandability, and also supports a preview function of interactive 3D stereoscopic image to determine stereoscopic view of high quality.

• Journal of radiological science and technology
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• v.44 no.1
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• pp.31-37
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• 2021

This study aim of quantitative assessment of Noise Power Spectrum(NPS) and image characteristics of by acquired the optimal image for noise characteristics and quality assurance by using magnetic resonance imaging(MRI). MRI device was (MAGNETOM Vida 3.0T MRI; Siemense healthcare system; Germany) used and the head/neck shim MR receive coil were 20 channels coil and a diameter 200 mm hemisphere phantom. Frequency signal could be acquired the K-space trajectory image and white image for NPS. The T2 image highest quantitatively value for NPS finding of showed the best value of 0.026 based on the T2 frequency of 1.0 mm-1. The NPS acquired of showed that the T1 CE turbo image was 0.077, the T1 CE Conca2 turbo image was 0.056, T1 turbo image was 0.061, and the T1 Conca2 turbo image was 0.066. The assessment of NPS image characteristics of this study were to that could be used efficiently of the MRI and to present the quantitative evaluation methods and image noise characteristics of 3.0T MRI.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.99-110
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• 2005

These days, many image processing techniques have been studied for effective image compression. Among those, The 2D image filtering is widely used for 2D image processing. The 2D image filtering can be implemented by performing the 1D linear filter separately in the horizontal and vertical direction. Efficiency of image compression depends on what filtering method is used. Generally, circular convolution is widely used in 2D image filtering for image processing. However it doesn't consider correlations at the boundary region of image, therefore effective filtering can not be performed. To solve this problem. I proposed new convolution technique using loop convolution which satisfies the 'alias-free' and 'error-free' requirement in the reconstructed image. This method could provide more effective compression performance than former methods because it used highly-correlated data when performed at the boundary region. In this paper, Sub-band Coding(SBC) was adopted to analyze efficiency of proposed filtering technique, and the simulator developed by Java-based language was used to examine the performance of proposed method.

• Journal of the Korean Society of Fashion and Beauty
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• v.2 no.3 s.3
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• pp.44-59
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• 2004

The purpose of this study was to find out proper evaluative words according to fashion image and to identify the correlation between clothing style and hair style related to fashion image. The questionnaire was used to collect data. 326 female aged between 23 to 40 were selected for the subjects of this study. The data were analyzed by frequency, factor analysis, pearsons correlation. The results of this study were as follows. 1. Evaluative words for each fashion image were selected by factor analysis. modern image intellectual, cold, urbane, simple, straight. elegance image : graceful, dignified, refined, decorous, luxurious. romantic image : cute, lovely, girlish, feminine, romantic. natural image : natural, comfortable, gentle, intimate, soft. casual image : energetic, active, free, cheerful, vivid. avant-garde image : experimental, strange, creative, avant-garde, irregular. 2. Correlation between clothing style image and hair style image ; clothing style and hair style was positively correlated. with the same image in case of modern, romantic, casual, elegance and avantgarde but natural image of clothing style was correlated with the natural, elegance, romantic, modern image of hair style. 3. The most suitable hair style for the clothing style according to fashion image : The clothing style of a particular image was matched best with the hair style of the same image.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.91-97
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• 2013

Image and it's processing techniques are widely applied and very important in the recent IT environment. In this paper, we try to reconstruct original BMP(Bitmap) image into indexed image and codebook utilizing vector quantization and represent high quality image only with same pixel depth of previous indexed image like JPEG etc. That is, By adopting common map method onto index image with $2^n$ color codebook, image can be represented as high quality as $2^{n+1}$ color codebook. When proposed output image is compared with original BMP image, it provides as much around 2dB as higher PSNR than conventional 8 bit index image(normal JPEG). Furthermore, this improvement(2 dB higher PSNR) could be provided when using the 9 bit indexed image.