• Progress in Medical Physics
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• v.33 no.4
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• pp.172-179
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• 2022

Recently, tetrahedral phantoms have been newly adopted as international standard mesh-type reference computational phantoms (MRCPs) by the International Commission on Radiological Protection, and a program has been developed to convert them to computational tomography images and DICOM-RT structure files for application of radiotherapy. Through this program, the use of the tetrahedral standard phantom has become available in clinical practice, but utilization has been difficult due to various library dependencies requiring a lot of time and effort for installation. To overcome this limitation, in this study a newly developed TET2DICOM-GUI, a TET2DICOM program based on a graphical user interface (GUI), was programmed using only the MATLAB language so that it can be used without additional library installation and configuration. The program runs in the same order as TET2DICOM and has been optimized to run on a personal computer in a GUI environment. A tetrahedron-based male international standard human phantom, MRCP-AM, was used to evaluate TET2DICOM-GUI. Conversion into a DICOM-RT dataset applicable in clinical practice in about one hour with a personal computer as a basis was confirmed. Also, the generated DICOM-RT dataset was confirmed to be effectively implemented in the radiotherapy planning system. The program developed in this study is expected to replace actual patient data in future studies.

• The Journal of Korean Academy of Prosthodontics
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• v.57 no.1
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• pp.57-65
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• 2019

Computer aided design and manufacturing and implant surgery using a guide template improve restoration-driven implant treatment procedures. This case utilized those digital technologies to make definitive prostheses for a patient. According to the work flow of digital dentistry, cone beam computed tomography established the treatment plan, which was followed to make the guide template for implant placement. The template guided the implants to be installed as planned. The customized abutments and surveyed fixed restorations were digitally designed and made. The metal framework of the removable partial denture was cast from resin pattern using an additive manufacturing technique, and the artificial resin teeth were replaced with the zirconia onlays for occlusal stability. These full mouth rehabilitation procedures provided functionally and aesthetically satisfactory results for the patient.

• Journal of Biomedical Engineering Research
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• v.22 no.3
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• pp.223-229
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• 2001

In this paper, we have compared the direct fan-beam reconstruction method with the rebinning method in terms of computation time and spatial resolution using computer simulation. As a result, the direct fan-beam method is superior to the rebinning method in the spatial resolution though the former needs longer computation time. However, if we adopt the quarter-detector-offset technique to improve the spatial resolution, the rebinning method outperforms the direct fan-beam method. The computation times have been evaluated using the fast algorithms optimized to reduce the number of interpolation calculations at the back-projection, and the spatial resolutions have been compared using the computer generated phantoms.

• Proceedings of the KOSOMBE Conference
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• v.1989 no.05
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• pp.39-43
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• 1989

In this paper, hierachical representation method with a 1-to-4 and 1-to-8 data structure is used to reconstruct the three-dimensional scene from two-dimensional cross sections provided by computed tomography with small memory computer system. To reduce the internal memory use, 2-D section is represented by quadtree, and 3-D scene is represented by octree. Octree is constructed by recursively merging consecutive quadtrees. This method uses 7/200 less memory than pointer type structure with all the case, and less memory up to 60.3% than linear octree with experimental data.

• Korean Journal of Computational Design and Engineering
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• v.14 no.1
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• pp.10-17
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• 2009

Surface detection and parameter estimation in point cloud is a relevant subject in CAD/CAM, reverse engineering, computer vision, coordinate metrology and digital factory. In this paper we present a software for a fully automatic surface detection and parameter estimation in unordered, incomplete and error-contaminated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting, which work interactively. Our newly developed algorithms for orthogonal distance fitting(ODF) play a fundamental role in each of the three modules. The ODF algorithms estimate the model parameters by minimizing the square sum of the shortest distances between the model feature and the measurement points. We demonstrate the performance of the software on a variety of point clouds generated by laser radar, computer tomography, and stripe-projection method.

• Journal of Magnetics
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• v.21 no.2
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• pp.204-208
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• 2016

This paper demonstrates the key parameter detection for smelting of submerged arc furnace (SAF) based on magnetic field radiation. A magnetic field radiation model for the inner structure of SAF is established based on relative theory of electromagnetic field. A simple equipment of 3D magnetic field detection system is developed by theoretical derivation and simulation. The experiments are carried out under the environment of industrial field and AC magnetic field generated by electrode currents and molten currents in the furnace is reflected outside of the furnace. The experimental results show that the key parameters of smelting including the position of electrode tip, the length of electric arc, and the liquid level of molten bath can be achieved. The computed tomography for SAF can be realized by the detection for smelting.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.703-705
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• 2005

본 논문에서는 기울기 크기 기반의 3차원 영역확장 알고리즘을 사용하여 small animal PET(Positron Emission Tomography) 영상으로부터 종양을 분할하는 연구를 수행하였다. 픽셀 값의 범위가 다양하고 저해상도의 특성을 갖는 PET영상으로부터 대상영역을 정확하게 분할하기 위해서 전처리(preprocessing)과정으로 영상 픽셀값의 분포를 펼쳐줌으로써 영상의 가시화를 높이는 히스토그램 스트레칭(histogram stretching) 기법을 적용하고 대상영역과 픽셀값이 유사한 인접영역과의 경계를 찾기 위해 가우시안의 1차 미분 함수를 사용하여 계산된 기울기 크기(gradient magnitude) 기반의 3차원 영역확장(region growing) 알고리즘을 제안한다. 제안한 알고리즘은 영역확장의 결과에 가장 큰 영향을 미치는 적절한 동질성 기준의 선택으로 대상영역의 분할을 성공적으로 수행하여 일반적인 영역확장의 단점을 보완하였다.

• Journal of Biomedical Engineering Research
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• v.15 no.2
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• pp.201-208
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• 1994

Many three-dimensional object modeling and display methods for computer graphics and computer vision have been developed. Recently, with the help of medical imaging devices such as computerized tomography, magnetic resonance image, etc., some of those object modeling and display methods have been widely used for capturing the shape, structure and other properties of real objects in many medical applications. In this paper, we propose the reconstruction and display method of the three-dimensional object from a series of the cross sectonal image. It is implemented by using the automatic threshold selection method and the contour following algorithm. The combination of curvature and distance, we select feature points. Those feature points are the candidates for the tiling method. As a results, it is proven that this proposed method is very effective and useful in the comprehension of the object's structure. Without the technician's responce, it can be automated.

• Journal of Multimedia Information System
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• v.8 no.4
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• pp.251-258
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• 2021

In 2019, a novel coronavirus (COVID-19) outbreak started in China and spread all over the world. The countries went into lockdown and closed their borders to minimize the spread of the virus. Shortage of testing kits and trained clinicians, motivate researchers and computer scientists to look for ways to automatically diagnose the COVID-19 patient using X-ray and ease the burden on the healthcare system. In recent years, multiple frameworks are presented but most of them are trained on a very small dataset which makes clinicians adamant to use it. In this paper, we have presented a lightweight deep learning base automatic COVID-19 detection system. We trained our model on more than 22,000 dataset X-ray samples. The proposed model achieved an overall accuracy of 96.88% with a sensitivity of 91.55%.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.326-327
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• 2007

We investigated whether the CT images of hepatic lesions could be analyzed by computer-aided diagnosis (CAD) tool. We retrospectively reanalyzed 14 liver CT images (10 hepatocellular cancers and 4 benign liver lesions; patients who presented with hepatic masses). The hepatic lesions on CT were segmented by rectangular ROI technique and the morphologic features were extracted and quantitated using fractal texture analysis. The contrast enhancement of hepatic lesions was also quantified and added to the differential diagnosis. The best discriminating function combining the textural features and the values of contrast enhancement of the lesions was created using linear discriminant analysis. Textural feature analysis showed moderate accuracy in the differential diagnosis of hepatic lesions, but statistically insignificant. Combining textural analysis and contrast enhancement value resulted in improved diagnostic accuracy, but further studies are needed.