• Progress in Medical Physics
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• v.21 no.1
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• pp.70-77
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• 2010

This study tested how S/N (Signal to Noise Ratio) ratios and ADC (apparent diffusion coefficient) values vary with different T-scores in a group of patients with osteoporosis. Based on DEXA (Dual Energy X-ray Absorptiometry) T-scores for L1.L4 for two groups of subjects consisting of 30 healthy people without osteoporosis and 30 patients who came for treatment of waist (lumbar or low back) pain and were suspected to have osteoporosis as judged from the simple X-ray findings, this study classified every spine into two groups of osteoporosis and osteopenia. Signal intensity measurements were made in the four regions of L1 to L4 on diffusion-weighted MR images obtained using 1.5T MR scanner, while ADC measurements were obtained from ADC map images. As an approach for quantitative analysis, the comparison of the variances in S/N ratios and ADC values for varying T-scores in the selected regions of interest was carried out based on averaged T-scores, S/N ratios, and ADC values. Also, the variances in S/N ratios and ADC values for each of the groups of osteoporosis and osteopenia, which were classified into by T-scores, were compared. For qualitative analysis, a careful naked eye examination of signal intensity differences in the area of L4 was made on T1-weighted sagittal images for each of the healthy (normal), osteopenia, and osteoporosis groups. In the qualitative analysis, it was found that for both the osteopenia group and the osteoporosis group, as T-scores deceased, the S/N ratios on diffusion-weighted MR images also decreased, with the greatest decrease in the S/N ratio found in the osteoporosis group. Additionally, among the three groups, the lowest S/N ratio was found in the osteoporosis group. With respect to ADC map, it was found that for both the osteopenia group and the osteoporosis group, as T-scores deceased, the ADC values on diffusion-weighted MR images also decreased, with the greatest decrease in the ADC values found in the osteoporosis group. Additionally, among the three groups, the lowest ADC value was found in the osteoporosis group. On the other hand, in the qualitative analysis, the osteoporosis group showed the highest signal intensity. Additionally, among the three groups, the lowest signal intensity was found in the healthy (normal) group. It was found that as osteoporosis progressed, S/N ratio and ADC decreased, whereas signal intensity increased on T1-weighted images. Also, in diagnosing osteoporosis, MRI tests turned out to be (more) effective.

• Journal of Yeungnam Medical Science
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• v.37 no.2
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• pp.90-97
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• 2020

Background: To minimize damage to the ovarian reserve, it is necessary to evaluate the follicular density in the ovarian tissue surrounding endometriosis on preoperative imaging. The purpose of the present study was to evaluate the usefulness of subtraction pelvic magnetic resonance imaging (MRI) to detect ovarian reserve. Methods: A subtracted T1-weighted image (^subT1WI) was obtained by subtracting unenhanced T1WI from contrast-enhanced T1WI (^ceT1WI) with similar parameters in 22 patients with ovarian endometriosis. The signal-to-noise ratio (SNR) in ovarian endometriosis, which was classified into the high signal intensity and iso-to-low signal intensity groups on the T2-weighted image, was compared to that in normal ovarian tissue. To evaluate the effect of contrast enhancement, a standardization map was obtained by dividing ^subT1WI by ^ceT1WI. Results: On visual assessment of 22 patients with ovarian endometriosis, 16 patients showed a high signal intensity, and 6 patients showed an iso-to-low signal intensity on T1WI. Although SNR in endometriosis with a high signal intensity was higher than that with an iso-to-low signal intensity, there was no difference in SNR after the subtraction (13.72±77.55 vs. 63.03±43.90, p=0.126). The area of the affected ovary was smaller than that of the normal ovary (121.10±22.48 vs. 380.51±75.87 ㎟, p=0.002), but the mean number of pixels in the viable remaining tissue of the affected ovary was similar to that of the normal ovary (0.53±0.09 vs. 0.47±0.09, p=0.682). Conclusion: The subtraction technique used with pelvic MRI could reveal the extent of endometrial invasion of the normal ovarian tissue and viable remnant ovarian tissue.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.133-134
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• 2014

Conventional stereo matching algorithms fail when they deal with anaglyph image as its input because anaglyph image does not have similar intensity on both view images. To ameliorate such problems, we propose a robust method to obtain accurate disparity maps. The novel Absolute Adaptive Normalized Cross Correlation (AANCC) for anaglyph data cost is introduced in this paper. Then, it is followed by occlusion detection and segmentation-based plane fitting to achieve accurate depth map acquisition. Experimental results confirm that the proposed anaglyph data cost is robust and gives accurate disparity maps.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1817_1818
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• 2009

Disparity 맵은 스테레오 카메라의 이미지 평면에 동일한 3차원 포인터를 나타내는 픽셀간의 차이를 나타내는 이미지이다. 이는 3차원 정보를 얻기 위하여 생성 한며 생성된 Disparity 맵은 Triangulation을 이용하여 3차원 복원이 가능하다. Disparity 맵은 픽셀의 intensity의 차를 이용하여 구하므로 Repeated Pattern 이나 Textureless 부분에서 많은 에러가 생기는 문제가 있다. 본 논문에서는 이런 문제점을 해결하기 위하여 싱글 카메라와 레이저 레인지 파인더의 캘리브레이션을 통해 알아낸 기하학적인 관계를 이용하여 3차원 정보를 카메라의 이미지 평면으로 역 사영 시켜서 Disparity 맵을 생성하는 알고리즘을 제안한다. 이 방법은 기존의 스트레오 카메라 기반으로 Disparity 맵을 생성하는 경우에 생기는 Repeated Pattern 이나 Textureless 부분의 문제를 해결 할 수 있다는 것을 실험을 통하여 검증 하였다.

• Publications of The Korean Astronomical Society
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• v.14 no.2
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• pp.79-81
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• 1999

We have made an extensive mapping of the $^{13}CO$ J=1-0 transition line in the dark cloud L1535. We also constructed the $100{\mu}m$ IRAS map in the region. We found a semi-detached cloud component of $^{13}CO$ in the northeast direction of the $^{13}CO$ main cloud which forms a dumbbell-like structure. This additional component with an angular size of $20'\times16'$ has not been observed before in any molecular surveys of the cloud. The IRAS map shows a similar structure with two intensity peaks whose positions coincide with those of the $^{13}CO$ clouds.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.51-56
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• 2018

This paper proposes the efficient preprocessing method based on curvelet transform for edge enhancement in image. The propose method is generated the edge map by using the Canny algorithm to wavelet transform, which is the sub-step of the curvelet transform. In order to improve the part of edge feature, the selective sharpening according to the generate edge map is applied. In experimental result, the propose method achieves that the enhancement of edge feature is better than conventional methods. This leads that peak to signal noise ratio, edge intensity are improvement on average about 1.92, 1.12dB respectively.

• Journal of Korea Game Society
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• v.20 no.3
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• pp.65-74
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• 2020

In the shadow map method, if the shadow map is magnified, the shadow has a jagged silhouette. Herein, we propose a soft shadow method that filters reshaped silhouettes analytically. First, the shadow silhouette is reshaped through sub-texel edge detection, which is based on linear or quadratic curve models. Second, an integral shadow filtering algorithm is used to accurately obtain the average shadow intensity from a definite integral estimation. The implementation demonstrates that our solution can effectively eliminate jagged aliasing and efficiently generate soft shadows.

• Korean Journal of Remote Sensing
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• v.21 no.5
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• pp.417-423
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• 2005

A fuzzy approach using an EM algorithm for image classification is presented. In this study, a double compound stochastic image process is assumed to combine a discrete-valued field for region-class processes and a continuous random field for observed intensity processes. The Markov random field is employed to characterize the geophysical connectedness of a digital image structure. The fuzzy classification is an EM iterative approach based on mixture probability distribution. Under the assumption of the double compound process, given an initial class map, this approach iteratively computes the fuzzy membership vectors in the E-step and the estimates of class-related parameters in the M-step. In the experiments with remotely sensed data, the MRF-based method yielded a spatially smooth class-map with more distinctive configuration of the classes than the non-MRF approach.

• Journal of Information Processing Systems
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• v.13 no.3
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• pp.448-463
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• 2017

Multimedia is a ubiquitous and indispensable part of our daily life and learning such as audio, image, and video. Objective and subjective quality evaluations play an important role in various multimedia applications. Blind image quality assessment (BIQA) is used to indicate the perceptual quality of a distorted image, while its reference image is not considered and used. Blur is one of the common image distortions. In this paper, we propose a novel BIQA index for Gaussian blur distortion based on the fact that images with different blur degree will have different changes through the same blur. We describe this discrimination from three aspects: color, edge, and structure. For color, we adopt color histogram; for edge, we use edge intensity map, and saliency map is used as the weighting function to be consistent with human visual system (HVS); for structure, we use structure tensor and structural similarity (SSIM) index. Numerous experiments based on four benchmark databases show that our proposed index is highly consistent with the subjective quality assessment.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.13-22
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• 2021

The ML 5.8 earthquake shocked Gyeongju, Korea, at 11:32:55 UTC on September 12, 2016. One year later, on the afternoon of November 15, 2017, the ML 5.4 earthquake occurred in Pohang, South Korea. The earthquakes injured many residents, damaged buildings, and affected the economy of Gyeongju and Pohang. The damage proxy maps (DPMs) were generated from Sentinel-1 synthetic aperture radar (SAR) imagery by comparing pre- and co-events interferometric coherences to identify anomalous changes that indicate damaged by the earthquakes. DPMs manage to detect coherence loss in residential and commercial areas in both Gyeongju and Pohang earthquakes. We found that our results show a good correlation with the Korea Meteorological Administration (KMA) report with Modified Mercalli Intensity (MMI) scale values of more than VII (seven). The color scale of Sentinel-1 DPMs indicates an increasingly significant change in the area covered by the pixel, delineating collapsed walls and roofs from the official report. The resulting maps can be used to assess the distribution of seismic damage after the Gyeongju and Pohang earthquakes and can also be used as inventory data of damaged buildings to map seismic vulnerability using machine learning in Gyeongju or Pohang.