• Korean Journal of Artificial Intelligence
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• v.9 no.2
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• pp.1-5
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• 2021

Although CT has an advantage in describing the three-dimensional anatomical structure of the human body, it also has a disadvantage in that high doses are exposed to the patient. Recently, a deep learning-based image reconstruction method has been used to reduce patient dose. The purpose of this study is to analyze the dose reduction and image quality improvement of deep learning-based reconstruction (DLR) on the adult's chest CT examination. Adult lung phantom was used for image acquisition and analysis. Lung phantom was scanned at ultra-low-dose (ULD), low-dose (LD), and standard dose (SD) modes, and images were reconstructed using FBP (Filtered back projection), IR (Iterative reconstruction), DLR (Deep learning reconstruction) algorithms. Image quality variations with respect to varying imaging doses were evaluated using noise and SNR. At ULD mode, the noise of the DLR image was reduced by 62.42% compared to the FBP image, and at SD mode, the SNR of the DLR image was increased by 159.60% compared to the SNR of the FBP image. Based on this study, it is anticipated that the DLR will not only substantially reduce the chest CT dose but also drastic improvement of the image quality.

• Imaging Science in Dentistry
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• v.40 no.2
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• pp.63-68
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• 2010

Purpose : To compare the CT numbers on 3 cone-beam CT (CBCT) images with those on multi-detector CT (MDCT) image using CT phantom and to develop linear regressive equations using CT numbers to material density for all the CT scanner each. Materials and Methods : Mini CT phantom comprised of five 1 inch thick cylindrical models with 1.125 inches diameter of materials with different densities (polyethylene, polystyrene, plastic water, nylon and acrylic) was used. It was scanned in 3 CBCTs (i-CAT, Alphard VEGA, Implagraphy SC) and 1 MDCT (Somatom Emotion). The images were saved as DICOM format and CT numbers were measured using OnDemand 3D. CT numbers obtained from CBCTs and MDCT images were compared and linear regression analysis was performed for the density, $\rho$ ($g/cm^3$), as the dependent variable in terms of the CT numbers obtained from CBCTs and MDCT images. Results : CT numbers on i-CAT and Implagraphy CBCT images were smaller than those on Somatom Emotion MDCT image (p<0.05). Linear relationship on a range of materials used for this study were $\rho$=0.001H+1.07 with $R^2$ value of 0.999 for Somatom Emotion, $\rho$=0.002H+1.09 with $R^2$ value of 0.991 for Alphard VEGA, $\rho$=0.001H+1.43 with $R^2$ value of 0.980 for i-CAT and $\rho$=0.001H+1.30 with $R^2$ value of 0.975 for Implagraphy. Conclusion: CT numbers on i-CAT and Implagraphy CBCT images were not same as those on Somatom Emotion MDCT image. The linear regressive equations to determine the density from the CT numbers with very high correlation coefficient were obtained on three CBCT and MDCT scan.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05a
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• pp.631-634
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• 2003

오늘날 CT나 MR등을 통한 의학 영상 기술과 컴퓨터 성능의 향상으로 인체 내부 장기의 영상을 비교적 용이하게 얻을 수 있으며 얻어진 영상 정보는 컴퓨터로 수치화 되므로 데이터의 조작 및 가공이 용이하다. 그러나, 이렇게 얻어진 의학 영상들은 보통 2 차원적 슬라이스 image 형태로 얻어진다. 일반적으로 슬라이스 사이의 간격은 조사량 등 여러 문제 때문에, 항상 동일한 간격을 유지하고 있지 않은 경우가 많으며 슬라이스 사이 간격이 슬라이스 내의 픽셀 간격보다 큰 경우가 대부분이다. 이러한 image로부터 3 차원적 디스플레이나, 조작, 분석을 하기 위해서는 같은 간격의 image를 얻어야 한다. 이러한 이유로 인하여 보간(Interpolation) 기법이 의학 영상 분야에서 많이 사용된다. 본 논문은 형태-기반 보간 방법을 gray-scale image 에 적용이 가능하도록 확장한 그레이 수준 형태 기반 보간 알고리즘을 구현하였다. 그리하여, 본 논문이 제안한 알고리즘을 슬라이스 간격이 큰 2차원 복부 CT 영상에 적용시켜 다른 보간 법들보다 향상된 결과를 확인할 수 있었다.

• Journal of Korea Multimedia Society
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• v.18 no.9
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• pp.997-1007
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• 2015

In this paper, we propose a method for automatically analyzing the bone formation in a mouse model of frontal bone defect. We perforate two holes of 0.8mm diameter in the frontal bone and observe the bone formation process using a micro CT. Because the conventional analysis software of the micro CT does not support automatic analysis of the bone formation status, we have to use a manual analysis method. However the manual analysis is very cumbersome and requires a lot of time, we propose an automatic analysis method. It rotates the image around three axes directions so that the mouse's skull come into regular position. It calculates the cumulative image of the voxel values for the perforated bone surface. It estimates the hole location by finding the darkest point in the cumulative image. The proposed method was applied to 24 CT images of saline administration group and PTH administration group and hole location was estimated. BV/TV index was calculated for the estimated hole to evaluate the bone formation status. Experimental results showed that bone formation process is more active in PTH administration group. The method proposed in this paper could replace successfully the cumbersome and time consuming manual job.

• The Korean Journal of Nuclear Medicine Technology
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• v.12 no.3
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• pp.214-221
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• 2008

Purpose: We make a qualitative analysis of whether Fusion SPECT/CT can find lesion's anatomical sites better than existing SPECT or not, and we want to show the usefulness of SPECT/CT through finding out effects of CT attenuation correction on SPECT images. Materials and Method: 1. The evaluation of fusion images: This study comprised patients who was tested $^{131}I$-MIBG, Bone, $^{111}In$-Octreotide, Meckel's diverticulum, Parathyroid MIBI with Precedence 16 or Symbia T2 from 2008 Jan to Aug. We compared SPECT/CT image with non fusion image and make a qualitative analysis. 2. The evaluation of attenuation correction: We classified 38 patients who was tested 201Tl myocardial exam with Symbia T2 into 5 sections by using Cedars Sinai' QPS program - Ant, Inf, Lat, Septum, Apex. And we showed each section's perfusion states by percentage. We compared the each section's perfusion-states differences between CT AC and Non AC by average${\pm}$standard deviation. Results: 1. The evaluation of fusion images : In high energy $^{131}I$ cases, it was hard to grasp exact anatomical lesions due to difference between regions and surrounding lesions' uptake level. After combining with CT, we could grabs anatomical lesion more exactly. And in meckel's diverticulum case or to find lesions around bowels or organs with $^{111}In$ cases, it demonstrates its superiority. Bone SPECT/CT images help to distinguish between disk spaces certainly and give correct results. 2. The evaluation of attenuation correction: There is no significant difference statistically in Ant and Lat (p>0.05), but there is a meaningful difference in Inferior, Apex and Septum (p<0.05). AC perfusion at inferior wall in the 5 sections of myocardium: The perfusion difference between Non AC perfusion image ($68.58{\pm}7.55$) and CT corrected perfusion image ($76.84{\pm}6.52$) was the largest by $8.26{\pm}4.95$ (p<0.01, t=10.29). Conclusion: Nuclear medicine physicians can identify not only molecular image which shows functional activity of lesions but also anatomical location information of lesions with more accuracy using the combination of SPECT and CT systems. Of course this combination helps nuclear medicine physician find out the abnormal parts. Moreover combined data sets help separate between normal group and abnormal group in complicated body part. So clinicians can carry out diagnosis and treatment planning at the same time with a single test image. In addition, when we examine a myocardium in thorax where attenuation can occur easily, we can trust perfusion more in a certain region in SPECT test because CT provides the capability for accurate attenuation correction. In these reasons, we think we can prove the justice after treatment fusion image.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.592-600
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• 2016

AAPM CT performance for special medical equipment quality control checks using a standard phantom for evaluation, using the evaluator's subjective assessment as to minimize errors due computerized assessment program to evaluate their usefulness. Phantom for evaluation AAPM CT Performance Phantom: was used, the default shooting conditions are the same as quality control checks. And, we use IMAGE J to evaluate the program. Quantitative evaluation with CT attenuation coefficient and the noise measurement, the uniformity measurement, the slice thickness measurement, contrast resolution of the measurement, a phantom image of the spatial resolution determined by the evaluation program is evaluated as self-extracting the result after processing the image, CT uniformity measurement for the evaluation that was smaller and the standard deviation of a video image processing more uniform slice thickness measurements it is difficult to evaluate due to the difference of the ratio of the measured value of the phantom image. Contrast resolution was measured cylindrical diameter 6th evaluate the shape of a circle obtained a mean value and a standard deviation of diameters, the spatial resolution of the group of source, including acceptance criteria automatically extracted result as a result of both the number of the extracted circularIt appeared. Evaluate the source image and video processing, and video to qualitative evaluation by gross were processed video image is shown excellent results. If the evaluators in order to minimize the errors of subjective judgment based on the results of the above should be done with a quantitative evaluation and qualitative evaluation utilizes a computerized assessment program is considered that further evaluation be made more efficient.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.123-131
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• 2019

In this study, we modified CT images of femoral head in consideration of anatomically meaningful structure, proposing the method to augment the training data of convolution Neural network for segmentation of femur mesh model. First, the femur mesh model is obtained from the CT image. Then divide the mesh model into meaningful parts by using cluster analysis on geometric characteristic of mesh surface. Finally, transform the segments by using an appropriate mesh deformation algorithm, then create new CT images by warping CT images accordingly. Deep learning models using the data enhancement methods of this study show better image division performance compared to data augmentation methods which have been commonly used, such as geometric conversion or color conversion.

• Journal of the Korean Society of Radiology
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• v.2 no.3
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• pp.5-9
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• 2008

In the computerized tomography(CT), various filters are using in the reconstruction algorithm to reduce or eliminate the artifacts which are intrinsically induced by the imperfection of mathematical methods for reconstruction, lack of real informations about anatomic structures in the projection image, errors in data acquisition and so on. Hann filter was used to evaluate the filter effects on the elimination of reconstruction artifact in the CT image. The quantitative study was done by changing cut-off frequency of Hann filter from 0.1 to 0.9 with frequency increasement by 0.2. NPS analysis was fulfilled for the quantitative evaluation of filter effect.

• Korean Journal of Artificial Intelligence
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• v.12 no.1
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• pp.1-6
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• 2024

Recently, various techniques are being applied through the development of medical AI, and research has been conducted on the application of super-resolution AI models. In this study, evaluate the results of the application of the super-resolution AI model to brain CT as the basic data for future research. Acquiring CT images of the brain, algorithm for brain and bone windowing setting, and the resolution was downscaled to 5 types resolution image based on the original resolution image, and then upscaled to resolution to create an LR image and used for network input with the original imaging. The SRCNN model was applied to each of these images and analyzed using PSNR, SSIM, Loss. As a result of quantitative index analysis, the results were the best at 256×256, the brain and bone window setting PSNR were the same at 33.72, 35.2, and SSIM at 0.98 respectively, and the loss was 0.0004 and 0.0003, respectively, showing relatively excellent performance in the bone window setting CT image. The possibility of future studies aimed image quality and exposure dose is confirmed, and additional studies that need to be verified are also presented, which can be used as basic data for the above studies.

• Nuclear Engineering and Technology
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• v.54 no.9
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• pp.3380-3389
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• 2022

We evaluated the performance of an improved hybrid median filter (IHMF) applied to X-ray computed tomography (CT) images obtained using a high-resolution photon-counting cadmium zinc telluride (CZT) detector. To study how the proposed approach improves the image quality, we measured the noise levels and the overall CT-image quality. We established a CZT imaging system with a detector length of 5.12 cm and thickness of 0.3 cm and acquired phantom images. To evaluate the efficacy of the proposed filter, we first modeled two conventional median filters. Subsequently, we were able to achieve a normalized noise power spectrum result of ~10^-8 mm², and furthermore, the proposed method improved the contrast-to-noise ratio by a factor of ~1.51 and the coefficient of variation by 1.55 relative to the counterpart values of the no-filter image. In addition, the IHMF exhibited the best performance among the three filters considered as regards the peak signal-to-noise ratio and no-reference-based image-quality evaluation parameters. Thus, our results demonstrate that the IHMF approach provides a superior image performance over conventional median filtering methods when applied to actual CZT X-ray CT images.