• Journal of International Society for Simulation Surgery
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• v.1 no.2
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• pp.83-86
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• 2014

Purpose This paper was purposed to suggest the method to produce the supportive helmet (head correction) for the infants who are suffering from plagiocephaly and to evaluate the level of transformation through 3D model. Method Either of CT or X-ray restored images has been used in making the supportive helmet (Head correction) in general, but these methods of measuring have problems in cost and safety. 3D surface measurement technology was suggested to solve such matters. Results It was to design the transformed model of the head within 0.7cm in average by scanning the surface of head and performing 3D restoration with marching cube and the changing rate of the head was compared in numerical data with 3D model. Conclusion The suggested methods displayed the better performance than the conventional method in respect of the speed and cost.

• Advances in biomechanics and applications
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• v.1 no.2
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• pp.111-126
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• 2014

The microarchitecture of trabecular bone plays a significant role in mechanical strength due to its load-bearing capability. However, the complexity of trabecular microarchitecture hinders the evaluation of its morphological characteristics. We therefore propose a new classification method based on static multiscale theory and dynamic finite element method (FEM) analysis to visualize a three-dimensional (3D) trabecular network for investigating the influence of trabecular microarchitecture on load-bearing capability. This method is applied to human vertebral trabecular bone images obtained by micro-computed tomography (micro-CT) through which primary trabecular bone is successfully visualized and extracted from a highly complicated microarchitecture. The morphological features were then analyzed by viewing the percolation of load pathways in the primary trabecular bone by using the stress wave propagation method analyzed under impact loading. We demonstrate that the present method is effective for describing the morphology of trabecular bone and has the potential for morphometric measurement applications.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.271-274
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• 1996

Shell rendering technique, which is the combined technique of surface rendering and volume rendering, was realized on workstation. By applying it to colon data acquired by CT, its validity was shown. In addition perspective projection coordinate was used for rendering the internal surface of organ and its reality was shown to be improved. This result can be use as the essential technique of virtual endoscope which is the recent hot topic in three dimensional medical imaging.

• Journal of Korean Neurosurgical Society
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• v.41 no.6
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• pp.418-420
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• 2007

Discal cyst is a very rare lesion that can result in refractory low back pain and leg radiating pain. Because they are so uncommon, their exact origin and pathophysiology are still unknown. A 31-year-old man visited our institute due to low back pain and severe left leg radiating pain. Magnetic resonance images [MRI] revealed spherically shaped extradural cystic lesion at L2-L3 level. Computed tomography [CT] discography demonstrated obvious communication between the intervertebral disc and the cyst. The patient underwent posterior decompression and excision of cyst. The symptoms were remarkably improved immediately after surgery.

• Journal of Korea Multimedia Society
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• v.24 no.4
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• pp.519-527
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• 2021

Alzheimer's disease is one of the challenges to tackle in the coming aging era and is attempting to diagnose and predict through various biomarkers. While the application of various deep learning-based technologies as powerful imaging technologies has recently expanded across the medical industry, empirical design is not easy because there are various deep earning neural networks architecture and categorical hyperparameters that rely on problems and data to solve. In this paper, we show the possibility of optimizing a deep learning neural network structure and hyperparameters for Alzheimer's disease classification in amyloid brain images in a representative deep earning neural networks architecture using genetic algorithms. It was observed that the optimal deep learning neural network structure and hyperparameter were chosen as the values of the experiment were converging.

• Journal of the Korean Society of Visualization
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• v.18 no.3
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• pp.96-102
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• 2020

Oral cancer surgery changes the morphologic characteristics of the human upper airway. These changes can affect the flow patterns. In this study, computational fluid dynamics (CFD) simulations with transient solver were performed to numerically investigate the air flows in the human upper airways depending oral cancer surgery. 3D reconstructed models were obtained from 2D CT images of one patient. For the boundary condition, the realistic breathing cycle of human was applied. The hydraulic diameters of cross-sections for post-surgical model are changed greatly along streamwise direction, so these variations can cause higher wall shear stress and flow disturbance compared to pre-surgical model. The recirculation flows observed in the protruding region result in the relatively large pressure drop. These results can be helpful to understand the flow variations after resection surgery of oral cancer.

• Investigative Magnetic Resonance Imaging
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• v.25 no.1
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• pp.47-52
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• 2021

Paraganglioma is a rare tumor of paraganglia, derived from neural crest cells in sympathetic or parasympathetic ganglions. It can be widely distributed from the skull base to the bottom of the pelvis. The pancreas, however, is a rare location of this neoplasm, and only a limited number of cases have been reported in the English literature, especially with gadoxetic-acid-enhanced magnetic resonance imaging (MRI) and diffusion-weighted images (DWI). We herein report a case of pathologically proven paraganglioma in the pancreas head with a literature review on endoscopic ultrasonography (EUS), computed tomography (CT), gadoxetic-acid-enhanced MRI, and DWI sequence.

• Annual Conference of KIPS
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• 2009.11a
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• pp.345-346
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• 2009

The segmentation of vessel including portal vein, hepatic vein and artery, from Computed Tomography (CT) images plays an important role in the therapeutic strategies for hepatic diseases. Representing segmented vessels in three dimensional spaces is extremely useful for doctors to plan liver surgery. In this paper, proposed method is focused on smoothing technique of segmented 3D liver vessels, which derived from 3D region growing approach. A pixel expand algorithm has been developed first to avoid vessel lose and disconnection cased by the next smoothing technique. And then a binary volume filtering technique has been implemented and applied to make the segmented binary vessel volume qualitatively smoother. This strategy uses an iterative relaxation process to extract isosurfaces from binary volumes while retaining anatomical structure and important features in the volume. Hard and irregular place in volume image has been eliminated as shown in the result part, which also demonstrated that proposed method is a suitable smoothing solution for post processing of fine vessel segmentation.

• Annual Conference of KIPS
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• 2023.05a
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• pp.539-541
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• 2023

COVID-19 is a viral pandemic disease that spreads widely all around the world. The only way to identify COVID-19 patients at an early stage is to stop the spread of the virus. Different approaches are used to diagnose, such as RT-PCR, Chest X-rays, and CT images. However, these are time-consuming and require a specialized lab. Therefore, there is a need to develop a time-efficient diagnosis method to detect COVID-19 patients. The proposed machine learning (ML) approach predicts the presence of coronavirus based on clinical symptoms. The clinical dataset is collected from the Israeli Ministry of Health. We used different ML classifiers (i.e., XGB, DT, RF, and NB) to diagnose COVID-19. Later, classifiers are optimized with the Bayesian hyperparameter optimization approach to improve the performance. The optimized RF outperformed the others and achieved an accuracy of 97.62% on the testing data that help the early diagnosis of COVID-19 patients.

• Korean Journal of Radiology
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• v.22 no.9
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• pp.1441-1450
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• 2021

Anomalous origin of the coronary artery from the pulmonary artery is a rare and potentially fatal congenital heart defect. Up to 90% of infants with an anomaly involving the left coronary artery die within the first year of life if left untreated. Patients who survive beyond infancy are at risk of sudden cardiac death. Cardiac CT and MRI are increasingly being used for the accurate diagnosis of this anomaly for prompt surgical restoration of the dual coronary artery system. Moreover, life-long imaging surveillance after surgery is necessary for these patients. In this pictorial review, multimodal cardiac imaging findings of this rare and potentially fatal coronary artery anomaly are comprehensively discussed, and representative images are provided to facilitate the understanding of this anomaly.