• The Journal of Korean Society for Radiation Therapy
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• v.22 no.2
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• pp.145-153
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• 2010

Purpose: To accurately define internal target volume (ITV) for treatment of moving target considering tumor size and respiratory motion, we quantitatively investigated volume of target volume delineated on CT images from helical CT and 4D CT scans. Materials and Methods: CT images for a 1D moving phantom with diameters of 1.5, 3, and 6 cm, acryl spheres were acquired using a LightSpeed $RT^{16}CT$ simulator. To analyze effect of tumor motion on target delineation, the CT image of the phantoms with various moving distances of 1~4 cm, and respiratory periods of 3~6 seconds, were acquired. For investigating the accuracy of the target trajectory, volume ratio of the target volumes delineated on CT images to expected volumes calculated with diameters of spherical phantom and moving distance were compared. Results: Ratio$_{helical}$ for the diameter of 1, 5, 3, and 6 cm targets were $32{\pm}14%$, $45{\pm}14%$, and $58{\pm}13%$, respectively, in the all cases. As to 4DCT, RatioMIP were $98{\pm}8%$, $97{\pm}5%$, and $95{\pm}1%$, respectively. Conclusion: The target volumes delineated on MIP images well represented the target trajectory, in comparison to those from helical CT. Target volume delineation on MIP images might be reasonable especially for treatment of early stage lung cancer, with meticulous attention to small size target, large respiratory motion, and fast breathing.

• Korean Journal of Computational Design and Engineering
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• v.15 no.4
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• pp.297-305
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• 2010

Medical image acquisition techniques such as CT and MRI have disadvantages in that the numerous time and efforts are needed. Furthermore, a great amount of radiation exposure is an inherent proberty of the CT imaging technique, a number of side-effects are expected from such method. To improve such conventional methods, a number of novel methods that can obtain 3D medical images from a few X-ray images, such as algebraic reconstruction technique (ART), have been developed. Such methods deform a generic model of the internal body part and fit them into the X-ray images to obtain the 3D model; the initial shape, therefore, affects the entire fitting process in a great deal. From this fact, we propose a novel method that can generate a 3D vertebraic generic model based on the statistical database of CT scans in this study. Moreover, we also discuss a method to generate patient-tailored generic model using the facts obtained from the statistical analysis. To do so, the mesh topologies of CT-scanned 3D vertebra models are modified to be identical to each other, and the database is constructed based on them. Furthermore, from the results of a statistical analysis on the database, the tendency of shape distribution is characterized, and the modeling parameters are extracted. By using these modeling parameters for generating the patient-tailored generic model, the computational speed and accuracy of ART can greatly be improved. Furthermore, although this study only includes an application to the C1 (Atlas) vertebra, the entire framework of our method can be applied to other body parts generally. Therefore, it is expected that the proposed method can benefit the various medical imaging applications.

• Journal of Broadcast Engineering
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• v.15 no.6
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• pp.723-730
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• 2010

Recently, diverse 3D image processing technologies have been applied in industries. Among them, stereoscopic conversion is a technology to generate a stereoscopic image from a conventional 2D image. The technology can be applied to movie and broadcasting contents and the viewer can watch 3D stereoscopic contents. Further the stereoscopic conversion is required to be applied to other fields. Following such trend, the aim of this paper is to apply the stereoscopic conversion to medical fields. The medical images can deliver more detailed 3D information with a stereoscopic image compared with a 2D plane image. This paper presents a novel methodology for converting a 2D medical image into a 3D stereoscopic image. For this, mean shift segmentation, edge detection, intensity analysis, etc are utilized to generate a final depth map. From an image and the depth map, left and right images are constructed. In the experiment, the proposed method is performed on a medical image such as CT (Computed Tomograpy). The stereoscopic image displayed on a 3D monitor shows a satisfactory performance.

• Journal of Biomedical Engineering Research
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• v.10 no.3
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• pp.317-322
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• 1989

In this paper, brain CT images are automatically segmented to reconstruct the 3-D scene from consecutive CT sections. Contextual segmentation technique was applied to overcome the partial volume artifact and statistical fluctuation phenomenon of soft tissue images. Images are hierarchically analyzed by region growing and graph editing techniques. Segmented regions are discriptively decided to the final organs by using the semantic informations.

• 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 the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.51-61
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• 2004

In the dental field, the 3D tooth model in which each tooth can be manipulated individually is an essential component for the simulation of orthodontic surgery and treatment. To reconstruct such a tooth model from CT slices, we need to define the accurate boundary of each tooth from CT slices. However, the global threshold method, which is commonly used in most existing 3D reconstruction systems, is not effective for the tooth segmentation in the CT image. In tooth CT slices, some teeth touch with other teeth and some are located inside of alveolar bone whose intensity is similar to that of teeth. In this paper, we propose an image segmentation algorithm based on B-spline curve fitting to produce smooth tooth regions from such CT slices. The proposed algorithm prevents the malfitting problem of the B-spline algorithm by providing accurate initial tooth boundary for the fitting process. This paper proposes an optimal threshold scheme using the intensity and shape information passed by previous slice for the initial boundary generation and an efficient B-spline fitting method based on genetic algorithm. The test result shows that the proposed method detects contour of the individual tooth successfully and can produce a smooth and accurate 3D tooth model for the simulation of orthodontic surgery and treatment.

• Imaging Science in Dentistry
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• v.40 no.2
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• pp.63-68
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• 2010

Purpose : To compare the CT numbers on 3 cone-beam CT (CBCT) images with those on multi-detector CT (MDCT) image using CT phantom and to develop linear regressive equations using CT numbers to material density for all the CT scanner each. Materials and Methods : Mini CT phantom comprised of five 1 inch thick cylindrical models with 1.125 inches diameter of materials with different densities (polyethylene, polystyrene, plastic water, nylon and acrylic) was used. It was scanned in 3 CBCTs (i-CAT, Alphard VEGA, Implagraphy SC) and 1 MDCT (Somatom Emotion). The images were saved as DICOM format and CT numbers were measured using OnDemand 3D. CT numbers obtained from CBCTs and MDCT images were compared and linear regression analysis was performed for the density, $\rho$ ($g/cm^3$), as the dependent variable in terms of the CT numbers obtained from CBCTs and MDCT images. Results : CT numbers on i-CAT and Implagraphy CBCT images were smaller than those on Somatom Emotion MDCT image (p<0.05). Linear relationship on a range of materials used for this study were $\rho$=0.001H+1.07 with $R^2$ value of 0.999 for Somatom Emotion, $\rho$=0.002H+1.09 with $R^2$ value of 0.991 for Alphard VEGA, $\rho$=0.001H+1.43 with $R^2$ value of 0.980 for i-CAT and $\rho$=0.001H+1.30 with $R^2$ value of 0.975 for Implagraphy. Conclusion: CT numbers on i-CAT and Implagraphy CBCT images were not same as those on Somatom Emotion MDCT image. The linear regressive equations to determine the density from the CT numbers with very high correlation coefficient were obtained on three CBCT and MDCT scan.

• Journal of the Korean Geotechnical Society
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• v.27 no.11
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• pp.93-101
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• 2011

High quality X-ray computed microtomography (micro-CT) imaging of internal microstructures and pore space in geomaterials is often hampered by some inherent noises embedded in the images. In this paper, we introduce image calibration techniques for removing the most common noises in X-ray micro-CT, cupping (brightness difference between the periphery and central regions) and ring artifacts (consecutive concentric circles emanating from the origin). The artifacts removal sequentially applies coordinate transformation, normalization, and low-pass filtering in 2D Fourier spectrum to raw CT-images. The applicability and performance of the techniques are showcased by describing extraction of 3D pore structures from micro-CT images of porous basalt using artifacts reductions, binarization, and volume stacking. Comparisions between calibrated and raw images indicate that the artifacts removal allows us to avoid the overestimation of porosity of imaged materials, and proper calibration of the artifacts plays a crucial role in using X-ray CT for geomaterials.

• Korean Journal of Radiology
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• v.22 no.6
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• pp.901-911
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• 2021

Objective: To evaluate the technical applicability of a semiautomatic three-dimensional (3D) hybrid CT segmentation method for the quantification of right ventricular mass in patients with cardiovascular disease. Materials and Methods: Cardiac CT (270 cardiac phases) was used to quantify right ventricular mass using a semiautomatic 3D hybrid segmentation method in 195 patients with cardiovascular disease. Data from 270 cardiac phases were divided into subgroups based on the extent of the segmentation error (no error; ≤ 10% error; > 10% error [technical failure]), defined as discontinuous areas in the right ventricular myocardium. The reproducibility of the right ventricular mass quantification was assessed. In patients with no error or < 10% error, the right ventricular mass was compared and correlated between paired end-systolic and end-diastolic data. The error rate and right ventricular mass were compared based on right ventricular hypertrophy groups. Results: The quantification of right ventricular mass was technically applicable in 96.3% (260/270) of CT data, with no error in 54.4% (147/270) and ≤ 10% error in 41.9% (113/270) of cases. Technical failure was observed in 3.7% (10/270) of cases. The reproducibility of the quantification was high (intraclass correlation coefficient = 0.999, p < 0.001). The indexed mass was significantly greater at end-systole than at end-diastole (45.9 ± 22.1 g/m² vs. 39.7 ± 20.2 g/m², p < 0.001), and paired values were highly correlated (r = 0.96, p < 0.001). Fewer errors were observed in severe right ventricular hypertrophy and at the end-systolic phase. The indexed right ventricular mass was significantly higher in severe right ventricular hypertrophy (p < 0.02), except in the comparison of the end-diastolic data between no hypertrophy and mild hypertrophy groups (p > 0.1). Conclusion: CT quantification of right ventricular mass using a semiautomatic 3D hybrid segmentation is technically applicable with high reproducibility in most patients with cardiovascular disease.

• 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.