• Progress in Medical Physics
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• v.7 no.1
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• pp.65-77
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• 1996

Using the 2-D and 3-D Hoffman brain phantom, 3-D Jaszczak phantom and Single Photon Emission Computed Tomography, the effects of data acquisition parameter, attenuation, noise, scatter and reconstruction algorithm on image quantitation as well as image quality were studied. For the data acquisition parameters, the images were acquired by changing the increment angle of rotation and the radius. The less increment angle of rotation resulted in superior image quality. Smaller radius from the center of rotation gave better image quality, since the resolution degraded as increasing the distance from detector to object increased. Using the flood data in Jaszczak phantom, the optimal attenuation coefficients were derived as 0.12cm$\^$-1/ for all collimators. Consequently, the all images were corrected for attenuation using the derived attenuation coefficients. It showed concave line profile without attenuation correction and flat line profile with attenuation correction in flood data obtained with jaszczak phantom. And the attenuation correction improved both image qulity and image quantitation. To study the effects of noise, the images were acquired for 1min, 2min, 5min, 10min, and 20min. The 20min image showed much better noise characteristics than 1min image indicating that increasing the counting time reduces the noise characteristics which follow the Poisson distribution. The images were also acquired using dual-energy windows, one for main photopeak and another one for scatter peak. The images were then compared with and without scatter correction. Scatter correction improved image quality so that the cold sphere and bar pattern in Jaszczak phantom were clearly visualized. Scatter correction was also applied to 3-D Hoffman brain phantom and resulted in better image quality. In conclusion, the SPECT images were significantly affected by the factors of data acquisition parameter, attenuation, noise, scatter, and reconstruction algorithm and these factors must be optimized or corrected to obtain the useful SPECT data in clinical applications.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.497-505
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• 2018

In a situation where the amount of bulky waste needs to be quantified, a three-dimensional model of the wastes can be constructed using drones. This study constructed a drone-based 3D model with a range of flight parameters and a GCPs survey, analyzed the relationship between the accuracy and time required, and derived a suitable drone application technique to estimate the amount of waste in a short time. Images of waste were photographed using the drone and auto-matching was performed to produce a model using 3D coordinates. The accuracy of the 3D model was evaluated by RMSE calculations. An analysis of the time required and the characteristics of the top 15 models with high accuracy showed that the time required for Model 1, which had the highest accuracy with an RMSE of 0.08, was 954.87 min. The RMSE of the 10th 3D model, which required the shortest time (98.27 min), was 0.15, which is not significantly different from that of the model with the highest accuracy. The most efficient flight parameters were a high overlapping ratio at a flight altitude of 150 m (60-70% overlap and 30-40% sidelap) and the minimum number of GCPs required for image matching was 10.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.393-400
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• 2021

Body weight of livestock is a crucial indicator for assessing feed requirements and nutritional status. This study was performed to estimate the body weight of Korean cattle (Hanwoo) using body volume determined from three-dimensional (3-D) image. A TOF camera with a resolution of 640×480 pixels, a frame rate of 44 fps and a field of view of 47°(H)×37°(V) was used to capture the 3-D images for Hanwoo. A grid image of the body was obtained through preprocessing such as separating the body from background and removing outliers from the obtained 3-D image. The body volume was determined by numerical integration using depth information to individual grid. The coefficient of determination for a linear regression model of body weight and body volume for calibration dataset was 0.8725. On the other hand, the coefficient of determination was 0.9083 in a multiple regression model for estimating body weight, in which the age of Hanwoo was added to the body volume as an explanatory variable. Mean absolute percentage error and root mean square error in the multiple regression model to estimate the body weight for validation dataset were 8.2% and 24.5kg, respectively. The performance of the regression model for weight estimation was improved and the effort required for estimating body weight could be reduced as the body volume of Hanwoo was used. From these results obtained, it was concluded that the body volume determined from 3-D of Hanwoo could be used as an effective variable for estimating body weight.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05c
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• pp.485-488
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• 2002

본 논문은 의학 연구 및 교육, 환자 치료를 위해 보다 정확한 정보를 제공하고자 의료 영상 중에 가장 많이 사용하는 의료 영상인 뇌 MR 영상의 횡단면만을 가지고 3차원으로 가시화한다. 3차원으로 재구성하는데 있어서 원 영상의 모형을 자연스러운 표현을 위해서는 층 영상과 층 영상간의 보간 영상이 필요하므로 이를 생성하는 방법에 대해서 제안한다. 그리고 3차원 재구성에 필요한 정보를 추출하기 위해 각 영상에서 머리와 뇌 영역의 윤곽선 정보를 추출하고 가시화의 시간을 줄이기 위해 윤곽선 정보에서 특징점을 추출하여 이를 기반으로 하여 3차원으로 재구성 한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.1025-1032
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• 2006

Sensor modeling of high-resolution satellites is a prerequisite procedure for mapping and GIS applications. Sensor models, describing the geometric relationship between scene and object, are divided into two main categories, which are rigorous and approximate sensor models. A rigorous model is based on the actual geometry of the image formation process, involving internal and external characteristics of the implemented sensor. However, approximate models require neither a comprehensive understanding of imaging geometry nor the internal and external characteristics of the imaging sensor, which has gathered a great interest within photogrammetric communities. This paper described a comparison between rigorous and various approximate sensor models that have been used to determine three-dimensional positions, and proposed the appropriate sensor model in terms of the satellite imagery usage. Through the case study of using IKONOS satellite scenes, rigorous and approximate sensor models have been compared and evaluated for the positional accuracy in terms of acquirable number of ground controls. Bias compensated RFM(Rational Function Model) turned out to be the best among compared approximate sensor models, both modified parallel projection and parallel-perspective model were able to be modelled with a small number of controls. Also affine transformation, one of the approximate sensor models, can be used to determine the planimetric position of high-resolution satellites and perform image registration between scenes.

• The korean journal of orthodontics
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• v.41 no.4
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• pp.255-267
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• 2011

Objective: The purpose of this study was to confirm the reliability of a cone beam computed tomography (CBCT)-generated panoramic view based on a CBCT 3D image and to find the most helpful 2D panoramic image compared with CBCT 3D image when examining the mesiodistal tooth axis. Methods: A test model was constructed according to cephalometric norms. The test model was repeatedly repositioned for CBCT and panoramic radiographic imaging. Panoramic radiographs were acquired at each of the following 3 occlusal plane positions: $-5^{\circ}$, $0^{\circ}$, and $+5^{\circ}$. Measurements of mesiodistal tooth axis in CBCT 3D image, CBCT-generated panoramic view, and panoramic radiographs were compared. Results: Compared with the CBCT-generated panoramic view, CBCT 3D image showed significant difference in the mesiodistal tooth axis in the premolars and no significant difference in the mesiodistal tooth axis in the incisors and canines. Mesiodistal tooth axis on the CBCT-generated panoramic view was significantly different from that on panoramic radiographs. Conclusions: CBCT-generated panoramic view can be a useful tool for evaluating mesiodistal tooth axis.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.335-339
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• 2005

Digital elevation models(DEM) were generated from SPOT-5 HRG supermode imagery through photogrammetric processing. The reference DEMs were obtained from digital topographic maps of 1/5000 scaleas for analyzing the accuracy of the generated DEMs. The DEMs extracted from HRG stereo image data were compared with digital topograpic map DEMs on several test sections. And digital surface models(DSM) and 3D building model was produced.

• Proceedings of the Korea Contents Association Conference
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• 2004.05a
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• pp.151-160
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• 2004

This research addresses the experimental application of the digital close-range photogrammetric technique for 3D deformation measurement and visualization of road slope. The 3D displacements were extracted by the photo-triangulation based on the bundle adjustment method using the digital imagery. In addition, we produced the digital elevation models, the digital orthorectified images and the 3D perspective view images of the slope employing a digital photogrammetric workstation. Also the inclination map of the slope was generated as the data for monitoring and managing dangerous slopes.

• Geophysics and Geophysical Exploration
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• v.4 no.1
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• pp.1-7
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• 2001

The application of geophysical survey methods need to be integrated to meet the increasing demands of imaging of the subsurface in the practical application of civil engineering, underground water survey and environmental problems. This paper examines the IP survey which can be surveyed simultaneously with DC resistivity survey. In this study, 3-D IP modeling algorithm was developed. The 3-D IP modeling algorithm was based on 3-D resistivity modeling by finite-element method. The result of 3-D modeling was compared with 2-dimensional modeling result. The result showed that the 3-D modeling algorithm developed in this study was accurate. Finally, the 3-D modeling algorithm developed in this paper will be useful for the study of IP data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.535-540
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• 2006

This paper presented an effective strategy to extract the buildings and to reconstruct 3-D buildings using high-resolution multispectral stereo satellite images. Proposed scheme contained three major steps: building enhancement and segmentation using both BDT (Background Discriminant Transformation) and ISODATA algorithm, conjugate building identification using the object matching with Hausdorff distance and color indexing, and 3-D building reconstruction using photogrammetric techniques. IKONOS multispectral stereo images were used to evaluate the scheme. As a result, the BDT technique was verified as an effective tool for enhancing building areas since BDT suppressed the dominance of background to enhance the building as a non-background. In building recognition, color information itself was not enough to identify the conjugate building pairs since most buildings are composed of similar materials such as concrete. When both Hausdorff distance for edge information and color indexing for color information were combined, most segmented buildings in the stereo images were correctly identified. Finally, 3-D building models were successfully generated using the space intersection by the forward RFM (Rational Function Model).