• Imaging Science in Dentistry
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• v.33 no.4
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• pp.199-205
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• 2003

Purpose: To compare the visibility of the mandibular canal at the different radiographic methods such as conventional panoramic radiographs, Vimplant multi planar reformatting (MPR)-CT panoramic images, Vimplant MPR-CT paraxial images and film-based DentaScan MPR-CT images. Materials and Methods: Data of 11 mandibular dental implant patients, who had been planned treatment utilizing both panoramic and MPR-CT examination with DentaScan software (GE Medical systems, Milwaukee, USA), were used in this study. The archived axial CT data stored on CD-R discs were transferred to a personal computer with 17' LCD monitor. Paraxial and panoramic images were reconstructed using Vimplant software (CyberMed Inc., Seoul, Korea). Conventional panoramic radiographs, monitor-based Vimplant MPR-CT panoramic images, monitor-based Vimplant MPR-CT paraxial images, and film-based DentaScan MPR-CT images were evaluated for visibility of the mandibular canal at the mental foramen, 1 cm, 2 cm, and 3 cm posterior to mental foramen using the 4-point grading score. Results: Vimplant MPR-CT panoramic, paraxial, and DentaScan MPR-CT images revealed significantly clearer images than conventional panoramic radiographs. Particularly at the region 1 em posterior to mental foramen, conventional panoramic radiographs showed a markedly lower percentage of 'excellent' mandibular canal images than images produced by other modalites. Vimplant MPR-CT and DentaScan MPR-CT images did not show significant difference in visibility of the mandibular canal. Conclusion: The study results show that Vimplant and DentaScan MPR-CT imaging systems offer significantly better images of the mandibular canal than conventional panoramic radiograph.

• Journal of Biomedical Engineering Research
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• v.15 no.2
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• pp.121-128
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• 1994

In this paper, MIlS (Medical Image Information System) has been designed and implemented using INGRES RDBMS, which is based on a client/server architecture. The implemnted system allows users to register and retrieve patient information, medical images and diagnostic reports. It also provides the function to display these information on workstation windows simultaneously by using the designed menu-driven graphic user interface. The medical image compression! decompression techniques are implemented and integrated into the medical image database system for the efficient data storage and the fast access through the network.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.1-9
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• 2010

Recently, 3D stereoscopic display such as 3D stereoscopic cinemas and 3D stereoscopic TV is getting a lot of interest. In general, a stereo image can be used in 3D stereoscopic display. In other hands, for 3D auto stereoscopic display, the elemental images should be generated through visualization from every camera in a lens array. Since a lens array consists of several cameras, it takes a lot of time to generate the elemental images with respect to 3D virtual space, specially, if a large bio-medical volume data is in the 3D virtual space, it will take more time. In order to improve the problem, in this paper, we construct an octree for a given bio-medical volume data and then propose a method to generate the elemental images through efficient rendering of the Octree data using GPU. Experimental results show that the proposed method can obtain more improvement comparable than conventional one, but the development of more efficient method is required.

• Radiation Oncology Journal
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• v.32 no.3
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• pp.116-124
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• 2014

Purpose: To investigate the frequency and clinical significance of detected incidental lung nodules found on computed tomography (CT) simulation images for hepatocellular carcinoma (HCC) using computer-aided diagnosis (CAD) and a physician review. Materials and Methods: Sixty-seven treatment-$na{\ddot{i}}ve$ HCC patients treated with transcatheter arterial chemoembolization and radiotherapy (RT) were included for the study. Portal phase of simulation CT images was used for CAD analysis and a physician review for lung nodule detection. For automated nodule detection, a commercially available CAD system was used. To assess the performance of lung nodule detection for lung metastasis, the sensitivity, negative predictive value (NPV), and positive predictive value (PPV) were calculated. Results: Forty-six patients had incidental nodules detected by CAD with a total of 109 nodules. Only 20 (18.3%) nodules were considered to be significant nodules by a physician review. The number of significant nodules detected by both of CAD or a physician review was 24 in 9 patients. Lung metastases developed in 11 of 46 patients who had any type of nodule. The sensitivities were 58.3% and 100% based on patient number and on the number of nodules, respectively. The NPVs were 91.4% and 100%, respectively. And the PPVs were 77.8% and 91.7%, respectively. Conclusion: Incidental detection of metastatic nodules was not an uncommon event. From our study, CAD could be applied to CT simulation images allowing for an increase in detection of metastatic nodules.

• Journal of the Korea Computer Graphics Society
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• v.23 no.2
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• pp.1-10
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• 2017

A variety of filters are applied to improve the quality of noise and low resolution medical images. This is necessary to reduce the radiation dose of the patient and to improve the utilization of the conventional spherical imaging equipment. In the conventional method, it is common to perform filtering using the CPU of the PC. However, it is difficult to produce results in real time by applying various calculations and filters to high-resolution human images using only the CPU performance of a PC used in a hospital. In this paper, we analyze the structure and performance of Intel integrated GPU in CPU and propose a method to perform image filtering using OpenCL parallel processing function. By applying complex filters with high computational complexity to medical images, high quality images can be generated in real time.

• Current Optics and Photonics
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• v.2 no.6
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• pp.499-507
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• 2018

For the spatiotemporally aligned observation of photothrombosis induction and transient variations of in vivo brain stroke, we developed a novel photothrombosis inducing system compatible to a magnetic resonance imaging (MRI) system using nonmagnetic stereotaxic equipment. From the spatial point of view, the system provides a more reliable level of reproducibility of the photothrombosis in each brain. From the temporal point of view, from T1- and T2-weighted in vivo MR (magnetic resonance) images, the transient variations such as incidence, location, and size of the thrombosis are measured quantitatively. In addition, the final variation is observed in the ex vivo brain by TTC (Triphenyltetrazolium chloride) staining based on histological assay and utilized for the verification of the MR images. From the experimental result of the rat brain, the proposed system shows more reliable characteristics for transient variations of brain strokes.

• Journal of radiological science and technology
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• v.32 no.2
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• pp.195-203
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• 2009

Image registration is a fundamental task in image processing used to match two or more images. It gives new information to the radiologists by matching images from different modalities. The objective of this study is to develop 2D image registration algorithm for PET/CT and CT images acquired by different systems at different times. We matched two CT images first (one from standalone CT and the other from PET/CT) that contain affluent anatomical information. Then, we geometrically transformed PET image according to the results of transformation parameters calculated by the previous step. We have used Affine transform to match the target and reference images. For the similarity measure, mutual information was explored. Use of particle swarm algorithm optimized the performance by finding the best matched parameter set within a reasonable amount of time. The results show good agreements of the images between PET/CT and CT. We expect the proposed algorithm can be used not only for PET/CT and CT image registration but also for different multi-modality imaging systems such as SPECT/CT, MRI/PET and so on.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.197-200
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• 2005

Super resolution image reconstruction method refers to image processing algorithms that produce a high resolution(HR) image from observed several low resolution(LR) images of the same scene. This method is proved to be useful in many practical cases where multiple frames of the same scene can be obtained, such as satellite imaging, video surveillance, video enhancement and restoration, digital mosaicking, and medical imaging. In this paper we applied super resolution reconstruction method in spatial domain to video sequences. Test images are adjacently sampled images from continuous video sequences and overlapped for high rate. We constructed the observation model between the HR images and LR images applied by the Maximum A Posteriori(MAP) reconstruction method that is one of the major methods in the super resolution grid construction. Based on this method, we reconstructed high resolution images from low resolution images and compared the results with those from other known interpolation methods.

• Korean Journal of Head & Neck Oncology
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• v.26 no.2
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• pp.193-197
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• 2010

Objectives : Patients with neck tumor and their family need every information about the disease. Especially, the size and location are confusing with verbal information. With the aid of CT, the problem had some answer, but it needs some medical education. We would like to know the usefullness of 3D reconstructed images in patient education about the disease. Material and Methods : Neck CT data were collected from 10 patients with various neck tumors and converted to 3D reconstructed images. Understanding of the patients about the size and location of tumors were rated from questionaires using axial CT images and 3D images. Results : Understanding score about 3D images were greater than that of CT images(p<0.006). Conclusion : 3D reconstructed images of CT could give the patients more real visual information about the disease.

• Journal of Biomedical Engineering Research
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• v.8 no.2
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• pp.171-176
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• 1987

Wiener filtering method was applied to the dual energy imaging procedure in digital radiography(D.R.). A linear scanning photodiode arrays with 1024 elements(0.6mm H 1.3mm pixel size) were used to obtain chest images in 0.7 sec. For high energy image acquisition, X-ray tube was set at 140KVp, 100mA with a rare-earth phosphor screen. Low energy image was obtained with X-ray tube setting at 70KVp, 150mA. These measured dual energy images are represented in the vector matrix notation as a linear discrete model including the additive random noise. Then, the object images are restored in the minimum mean square error sense using Wiener filtering method in the transformed domain. These restored high and low energy images are used for computation of the basis image decomposition. Then the basis images are linearly combined to produce bone or tissue selective images. Using this process, we could improve the signal to noise ratio characteristics in the material selective images.