• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.429-431
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• 2002

Metabolic analysis of biological tissues, the interventional radiology in MRT (Magnetic Resonance Treatment) and for clinical diagnoses, representation of 4-Dimensional (4D) structural information (x,y,z,t) of biological tissues is required. This paper discusses image representation techniques for those 4D MR Images. We have proposed an image reconstruction method for ultra-fast 3D MRI. It is based on image interpolation and prediction of un-acquired pictorial data in both of the real and the k-space (the acquisition domain in MRI). A 4D MR image is reconstructed from only two 3D MR images and acquired a few echo signals that are optimized by prediction of the tissue motion. This prediction can be done by the phase of acquired echo signal is proportioned to the tissue motion. On the other hand, reconstructed 4D MR images are represented as a 3D-movie by using computer graphics techniques. Rendered tissue surfaces and/or ROIs are displayed on a CRT monitor. It is represented in an arbitrary plane and/or rendered surface with their motion. As examples of the proposed representation techniques, the finger and the lung motion of healthy volunteers are demonstrated.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.977-991
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• 2000

In this paper, a medical image processing system was designed and implemented for morphometric and functional analysis of a human brain. The system is composed of image registration, ROI(region of interest) analysis, functional analysis, image visualization, 3D medical image database management system(DBMS), and database. The software processes an anatomical and functional image as input data, and provides visual and quantitative results. Input data and intermediate or final output data are stored to the database as several data types by the DBMS for other further image processing. In the experiment, the ROI analysis, for a normal, a tumor, a Parkinson's decease, and a depression case, showed that the system is useful for morphometric and functional analysis of a human brain.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.7
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• pp.834-850
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• 2011

In this paper, a novel tissue engineering scaffold design method based on triply periodic minimal surface (TPMS) is proposed. After generating the hexahedral elements for a 3D anatomical shape using the distance field algorithm, the unit cell libraries composed of triply periodic minimal surfaces are mapped into the subdivided hexahedral elements using the shape function widely used in the finite element method. In addition, a heterogeneous implicit solid representation method is introduced to design a 3D (Three-dimensional) bio-mimetic scaffold for tissue engineering from a sequence of computed tomography (CT) medical image data. CT image of a human spine bone is used as the case study for designing a 3D bio-mimetic scaffold model from CT image data.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.1
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• pp.59-67
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• 2014

Purpose : This study aims to evaluate 3D dosimetric impact for MIP image and each phase image in stereotactic body radiotherapy (SBRT) for lung cancer using volumetric modulated arc therapy (VMAT). Materials and Methods : For each of 5 patients with non-small-cell pulmonary tumors, a respiration-correlated four-dimensional computed tomography (4DCT) study was performed. We obtain ten 3D CT images corresponding to phases of a breathing cycle. Treatment plans were generated using MIP CT image and each phases 3D CT. We performed the dose verification of the TPS with use of the Ion chamber and COMPASS. The dose distribution that were 3D reconstructed using MIP CT image compared with dose distribution on the corresponding phase of the 4D CT data. Results : Gamma evaluation was performed to evaluate the accuracy of dose delivery for MIP CT data and 4D CT data of 5 patients. The average percentage of points passing the gamma criteria of 2 mm/2% about 99%. The average Homogeneity Index difference between MIP and each 3D data of patient dose was 0.03~0.04. The average difference between PTV maximum dose was 3.30 cGy, The average different Spinal Coad dose was 3.30 cGy, The average of difference with $V_{20}$, $V_{10}$, $V_5$ of Lung was -0.04%~2.32%. The average Homogeneity Index difference between MIP and each phase 3d data of all patient was -0.03~0.03. The average PTV maximum dose difference was minimum for 10% phase and maximum for 70% phase. The average Spain cord maximum dose difference was minimum for 0% phase and maximum for 50% phase. The average difference of $V_{20}$, $V_{10}$, $V_5$ of Lung show bo certain trend. Conclusion : There is no tendency of dose difference between MIP with 3D CT data of each phase. But there are appreciable difference for specific phase. It is need to study about patient group which has similar tumor location and breathing motion. Then we compare with dose distribution for each phase 3D image data or MIP image data. we will determine appropriate image data for treatment plan.

• Journal of Multimedia Information System
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• v.5 no.1
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• pp.35-42
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• 2018

Direct volume rendering (DVR) is an important 3D visualization method for medical images as it depicts the full volumetric data. However, because DVR renders the whole volume, regions of interests (ROIs) such as a tumor that are embedded within the volume maybe occluded from view. Thus, conventional 2D cross-sectional views are still widely used, while the advantages of the DVR are often neglected. In this study, we propose a new visualization algorithm where we augment the 2D slice of interest (SOI) from an image volume with volumetric information derived from the DVR of the same volume. Our occlusion-based DVR augmentation for SOI (ODAS) uses the occlusion information derived from the voxels in front of the SOI to calculate a depth parameter that controls the amount of DVR visibility which is used to provide 3D spatial cues while not impairing the visibility of the SOI. We outline the capabilities of our ODAS and through a variety of computer tomography (CT) medical image examples, compare it to a conventional fusion of the SOI and the clipped DVR.

• Journal of Biomedical Engineering Research
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• v.24 no.4
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• pp.247-257
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• 2003

This paper proposes a three-dimensional (3D) segmentation algorithm for extracting a diagnostic object from ultrasound images by using a LoG operator In the proposed algorithm, 2D cutting planes are first obtained by the equiangular revolution of a cross sectional Plane on a reference axis for a 3D volume data. In each 2D ultrasound image. a region of interest (ROI) box that is included tightly in a diagnostic object of interest is set. Inside the ROI box, a LoG operator, where the value of $\sigma$ is adaptively selected by the distance between reference points and the variance of the 2D image, extracts edges in the 2D image. In Post processing. regions of the edge image are found out by region filling, small regions in the region filled image are removed. and the contour image of the object is obtained by morphological opening finally. a 3D volume of the diagnostic object is rendered from the set of contour images obtained by post-processing. Experimental results for a tumor and gall bladder volume data show that the proposed method yields on average two times reduction in error rate over Krivanek's method when the results obtained manually are used as a reference data.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.119-122
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• 1997

In this paper, we represented the variation of heart cavity area in the space domain by 3-d rendering. We arranged the 2-d sequence of ultrasonic image acquired in the time domain as volumetric data, and extracted heart cavity region from 3-d data. For the segmentation of 3-d volume data, we extracted the cavity region using the method of expanding the cavity region that is same statistical property. By shading which is using light and object normal vector, we visualized the volume data on image plane.

• Journal of Korea Multimedia Society
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• v.5 no.5
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• pp.494-504
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• 2002

Volume rendering is a method of displaying volumetric data as a sequence two-dimensional image. Because this algorithm has an advantage of visualizing structures within objects, it has recently been used to analyze medical images i.e, MRI, PET, and SPECT. In this paper. we suggested a method for creating images easily from sampled volumetric data and applied the interpolation method to medical images. Additionally, we implemented and applied two kinds of interpolation methods to improve the image quality, linear interpolation and cubic interpolation at the sampling stage. Subsequently, we compared the results of volume rendered data using a transfer function. We anticipate a significant contribution to diagnosis through image reconstruction using a volumetric data set, because volume rendering techniques of medical images are the result of 3-dimensional data.

• 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.

• The Korean Journal of Emergency Medical Services
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• v.18 no.3
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• pp.63-75
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• 2014

Purpose: The purpose of this study was to investigate the image about emergency medical technology (EMT) jobs and to identify factors influencing the image of EMT jobs among students of this department. Methods: A self-reported questionnaire was administered to 532 paramedic students in the cities of D, G, and J between May 28 and June 19, 2013. Data were analyzed by using the SPSS version 21.0 program. Results: The image about EMT jobs was positively related to self-esteem. However, the image about EMT jobs was negatively related to grade and hospital practice experience. In the multiple regression analysis, the adjusted $R^2$ value was .220 (p < .001). Conclusion: The importance of enhancing the self-esteem of paramedic students should be emphasized. Further research on the image about EMT jobs in the hospital practice setting is needed.