• Journal of the Korean Society for Precision Engineering
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• v.23 no.11 s.188
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• pp.93-102
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• 2006

In this study an advanced domain decomposition method is suggested in order to construct surface models from very large amount of points. In this method the spatial domain of interest that is occupied by the input set of points is divided in repetitive manner. First, the space is divided into smaller domains where the problem can be solved independently. Then each subdomain is again divided into much smaller domains where the problem can be solved locally. These local solutions of subdivided domains are blended together to obtain a solution of each subdomain using partition of unity function. Then the solutions of subdomains are merged together in order to construct whole surface model. The suggested methods are conceptually very simple and easy to implement. Since RDDM(Repetitive Domain Decomposition Method) is effective in the computation time and memory consumption, the present study is capable of providing a fast and accurate reconstructions of complex shapes from large amount of point data containing millions of points. The effectiveness and validity of the suggested methods are demonstrated by performing numerical experiments for the various types of point data.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.6
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• pp.511-520
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• 2009

In this paper, we present a new iso-density surface reconstruction scheme based on a hierarchy on the input volume data and the output mesh data. From the input volume data, we construct a hierarchy of volumes, called a volume pyramid, based on a 3D dilation filter. After constructing the volume pyramid, we extract a coarse base mesh from the coarsest resolution of the pyramid with the Cell-boundary representation scheme. We iteratively fit this mesh to the iso-points extracted from the volume data under O(3)-adjacency constraint. For the surface fitting, the shrinking process and the smoothing process are adopted as in the SWIS (Shrink-wrapped isosurface) algorithm[6], and we subdivide the mesh to be able to reconstruct fine detail of the isosurface. The advantage of our method is that it generates a mesh which can be utilized by several multiresolution algorithms such as compression and progressive transmission.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.2 s.95
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• pp.116-122
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• 1999

저차 동적계(특히 카오스계)에서 측정한 시계열의 잡음을 제거하기 위해서 SVD(Singular Value Decomposotion)을 이용한 새로운 간편하고 매우 효과적인 새로운 잡음 제거법이 소개되었다. 이 방법은 위상궤적(phase portraint)을 재구성하는데 중점을 두었으며, 궤적행렬(trajectory matrix)을 구성하는데 그 기본을 두었다. 이 궤적행렬에 SVD를 반복적으로 사용하여 신호와 잡음을 분리하였다. 이 방법은 Duffing계에서 측정한 잡음이 섞인 카오스 신호에 적용되었으며, 또한 실험에 의한 진폭변조된 신호에도 적용되었다.

• Journal of Biomedical Engineering Research
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• v.20 no.6
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• pp.523-529
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• 1999

방출컴퓨터단층영상술을 위한 영상재구성법에 있어서 기대값 최대화(EM)를 사용한 maximum likeihood 방법이 기존의 filtered backprojection 방법에 비해 현저한 장점을 지니고 있다는 점에서 지속적으로 그 가치가 인정되어 왔다. 그러나, 이러한 방법은 projection 및 backprojection 의 반복계산을 요하므로 영상재구성을 위한 총 계산시간이 projector 및 backprojector 의 성능에 크게 좌우된다. 본 논문에서는 EM에 근거한 영상재구성 알고리즘의 계산량을 감소시키는 방법에 관하여 논한다. 특히, projection 및 backprojection 계산을 위한 행렬의 원소중 중요한 양들을 구하는 방법과 이들을 미리 계산하여 적절한 양의 메모리에 저장하는 방법에 관하여 고찰한다. 실험에서 제안된 방법을 사용할 경우 EM 알고리즘의 계산시간을 92%까지 현저히 감소시킬 수있음을 보였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2002.11a
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• pp.49-55
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• 2002

기존의 영상 획득 시스템들이 어느 정도의 엘리어싱을 허용하도록 제작되어왔음에도 불구하고, 고해상도 영상에 대한 요구는 점점 더 증가하고 있다. 본 논문에서는 부정확한 부화소 단위의 위치추정 오류를 고려한 고해상도 재구성 알고리즘을 제안한다. 부정확한 부화소 위치 추정 오류로 인해 생기는 불량위치문제(ill-posedness)를 해결하기 위해 정규화된 반복 연산법을 적용하였다. 특히 여러장의 저해상도 영상들을 개별적으로 고려하기에 적합한 다중채널 영상 재구성 방법을 도입하였다. 각 저해상도 영상에서 발생하는 움직임 추정오류는 서로 다른 경향성을 나타내므로, 정규화 파라미터들은 각 채널에 맞게 결정되어야 한다. 이를 위채 정규화 파라미터들을 자동으로 결정하는 방법을 제안한다. 제안한 알고리즘은 움직임 추정 오류에 매우 안정하며, 원 영상과 잡음에 대한 사전정보를 필요로 하지 않는다. 또한 주관적인 측면과 객관적인 측면에서 모두 우수한 결과를 실험적으로 보인다.

• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.297-303
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• 2023

Pediatric Computed Tomography (CT) examinations can often result in exam failures or the need for frequent retests due to the difficulty of cooperation from young patients. Deep Learning Image Reconstruction (DLIR) methods offer the potential to obtain diagnostically valuable images while reducing the retest rate in CT examinations of pediatric patients with high radiation sensitivity. In this study, we investigated the possibility of applying DLIR to reduce artifacts caused by respiration or motion and obtain clinically useful images in pediatric chest CT examinations. Retrospective analysis was conducted on chest CT examination data of 43 children under the age of 7 from P Hospital in Gyeongsangnam-do. The images reconstructed using Filtered Back Projection (FBP), Adaptive Statistical Iterative Reconstruction (ASIR-50), and the deep learning algorithm TrueFidelity-Middle (TF-M) were compared. Regions of interest (ROI) were drawn on the right ascending aorta (AA) and back muscle (BM) in contrast-enhanced chest images, and noise (standard deviation, SD) was measured using Hounsfield units (HU) in each image. Statistical analysis was performed using SPSS (ver. 22.0), analyzing the mean values of the three measurements with one-way analysis of variance (ANOVA). The results showed that the SD values for AA were FBP=25.65±3.75, ASIR-50=19.08±3.93, and TF-M=17.05±4.45 (F=66.72, p=0.00), while the SD values for BM were FBP=26.64±3.81, ASIR-50=19.19±3.37, and TF-M=19.87±4.25 (F=49.54, p=0.00). Post-hoc tests revealed significant differences among the three groups. DLIR using TF-M demonstrated significantly lower noise values compared to conventional reconstruction methods. Therefore, the application of the deep learning algorithm TrueFidelity-Middle (TF-M) is expected to be clinically valuable in pediatric chest CT examinations by reducing the degradation of image quality caused by respiration or motion.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3C
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• pp.288-296
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• 2009

In POCS (projection onto convex sets)-based reconstruction of HR (high resolution) image, the quality of reconstructed image is gradually improved through iterative motion estimation and image restoration. The amount of computation, however, increases because of the repeated inter-frame motion estimation. In this paper, an HR reconstruction algorithm is proposed where modified ARPS (adaptive rood pattern search) and POCS are simultaneously performed. In the modified ARPS, the motion estimates obtained from phase correlation or from the previous steps in POCS restoration are utilized as the initial reference in the motion estimation. Moreover, estimated motion is regularized with reference to the neighboring blocks' motion to enhance the reliability. Computer simulation results show that, when compared to conventional methods which are composed of full search block matching and POCS restoration, the proposed method is about 30 times faster and yet produces HR images of almost equal or better quality.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.1
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• pp.9-14
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• 2009

Purpose: Nowadays in the nuclear medicine, many studies and efforts are being made to reduce the scan time, as well as the waiting time to be needed to execute exams after injection of radionuclide medicines. Several methods are being used in clinic, such as developing new radionuclide compounds that enable to be absorbed into target organs more quickly and reducing acquisition scan time by increase the number of Gamma Camera detectors to examine. Each medical equipment manufacturer has improved the imaging process techniques to reduce scan time. In this paper, we tried to analyze the difference of image quality between FBP, 3D OSEM reconstruction methods that commercialized and being clinically applied, and Astonish reconstruction method (A kind of Iterative fast reconstruction method of Philips), also difference of image quality on scan time. Material and Methods: We investigated in 32 patients that examined the Bone SPECT from June to July 2008 at department of nuclear medicine, ASAN Medical Center in Seoul. 40sec/frame and 20sec/frame images were acquired that using Philips‘ PRECEDENCE 16 Gamma Camera and then reconstructed those images by using the Astonish (Philips’ Reconstruction Method), 3D OSEM and FBP methods. The blinded test was performed to the clinical interpreting physicians with all images analyzed by each reconstruction method for qualitative analysis. And we analyzed target to non target ratio by draws lesions as the center of disease for quantitative analysis. At this time, each image was analyzed with same location and size of ROI. Results: In a qualitative analysis, there was no significant difference by acquisition time changes in image quality. In a quantitative analysis, the images reconstructed Astonish method showed good quality due to better sharpness and distinguish sharply between lesions and peripheral lesions. After measuring each mean value and standard deviation value of target to non target ratio with 40 sec/frame and 20sec/frame images, those values are Astonish (40 sec-$13.91{\pm}5.62$ : 20 sec-$13.88{\pm}5.92$), 3D OSEM (40 sec-$10.60{\pm}3.55$ : 20 sec-$10.55{\pm}3.64$), FBP (40 sec-$8.30{\pm}4.44$ : 20 sec-$8.19{\pm}4.20$). We analyzed target to non target ratio from 20 sec and 40 sec images. And we analyzed the result, In Astonish (t=0.16, p=0.872), 3D OSEM (t=0.51, p=0.610), FBP (t=0.73, p=0.469) methods, there was no significant difference statistically by acquisition time change in image quality. But FBP indicates no statistical differences while some images indicate difference between 40 sec/frame and 20 sec/frame images by various factors. Conclusions: In the circumstance, try to find a solution to reduce nuclear medicine scan time, the development of nuclear medicine equipment hardware has decreased while software has marched forward at a relentless. Due to development of computer hardware, the image reconstruction time was reduced and the expanded capacity to restore enables iterative methods that couldn't be performed before due to technical limits. As imaging process technique developed, it reduced scan time and we could observe that image quality keep similar level. While keeping exam quality and reducing scan time can induce the reduction of patient's pain and sensory waiting time, also accessibility of nuclear medicine exam will be improved and it provide better service to patients and clinical physician who order exams. Consequently, those things make the image of department of nuclear medicine be improved. Concurrent Imaging - A new function that setting up each image acquisition parameter and enables to acquire images simultaneously with various parameters to once examine.

• Journal of radiological science and technology
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• v.40 no.2
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• pp.261-267
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• 2017

The study has attempted to evaluate and compare the image evaluation and exposure dose by respectively applying filter back projection (FBP), the existing test method, and adaptive statistical iterative reconstruction (ASIR) with different values of tube voltage during the low dose computed tomography (LDCT). With the image reconstruction method as basis, chest phantom was utilized with the FBP and ASIR set at 10%, 20% respectively, and the change of tube voltage (100 kVp, 120 kVp). For image evaluation, back ground noise, signal-noise ratio (SNR) and contrast-noise ratio (CNR) were measured, and, for dose assessment, CTDIvol and DLP were measured respectively. In terms of image evaluation, there was significant difference in ascending aorta (AA) SNR and inpraspinatus muscle (IM) SNR with the different amount of tube voltage (p < 0.05). In terms of CTDIvol, the measured values with the same tube voltage of 120 kVp were 2.6 mGy with no-ASIR and 2.17 mGy with 20%-ASIR respectively, decreased by 0.43 mGy, and the values with 100 kVp were 1.61 mGy with no-ASIR and 1.34 mGy with 20%-ASIR, decreased by 0.27 mGy. In terms of DLP, the measured values with 120 kVp were $103.21mGy{\cdot}cm$ with no-ASIR and $85.94mGy{\cdot}cm$ with 20%-ASIR, decreased by $17.27mGy{\cdot}cm$ (about 16.7%), and the values with 100 kVp were $63.84mGy{\cdot}cm$ with no-ASIR and $53.25mGy{\cdot}cm$ with 20%-ASIR, a decrease by $10.62mGy{\cdot}cm$ (about 16.7%). At lower tube voltage, the rate of dose significantly decreased, but the negative effects on image evaluation was shown due to the increase of noise.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.1
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• pp.17-24
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• 2011

Purpose: Presently in the nuclear medicine field, the high-speed image reconstruction algorithm like the OSEM algorithm is widely used as the alternative of the filtered back projection method due to the rapid development and application of the digital computer. There is no to relate and if it applies the optimal parameter be clearly determined. In this research, the quality change of the Jaszczak phantom experiment and brain SPECT patient data according to the iteration times and subset number change try to be been put through and analyzed in 3D OSEM reconstruction method of applying 3D beam modeling. Materials and Methods: Patient data from August, 2010 studied and analyzed against 5 patients implementing the brain SPECT until september, 2010 in the nuclear medicine department of ASAN medical center. The phantom image used the mixed Jaszczak phantom equally and obtained the water and 99mTc (500 MBq) in the dual head gamma camera Symbia T2 of Siemens. When reconstructing each image altogether with patient data and phantom data, we changed iteration number as 1, 4, 8, 12, 24 and 30 times and subset number as 2, 4, 8, 16 and 32 times. We reconstructed in reconstructed each image, the variation coefficient for guessing about noise of images and image contrast, FWHM were produced and compared. Results: In patients and phantom experiment data, a contrast and spatial resolution of an image showed the tendency to increase linearly altogether according to the increment of the iteration times and subset number but the variation coefficient did not show the tendency to be improved according to the increase of two parameters. In the comparison according to the scan time, the image contrast and FWHM showed altogether the result of being linearly improved according to the iteration times and subset number increase in projection per 10, 20 and 30 second image but the variation coefficient did not show the tendency to be improved. Conclusion: The linear relationship of the image contrast improved in 3D OSEM reconstruction method image of applying 3D beam modeling through this experiment like the existing 1D and 2D OSEM reconfiguration method according to the iteration times and subset number increase could be confirmed. However, this is simple phantom experiment and the result of obtaining by the some patients limited range and the various variables can be existed. So for generalizing this based on this results of this experiment, there is the excessiveness and the evaluation about 3D OSEM reconfiguration method should be additionally made through experiments after this.