• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.11 s.254
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• pp.1051-1056
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• 2006

The mean and RMS velocity field of the respiratory gas flow in the human airway was studied experimentally by particle image velocimetry (PIV). Some researchers investigated the airflow for the mouth breathing case both experimentally and numerically. But it is very rare to investigate the airflow of nose breathing in a whole airway due to its geometric complexity. We established the procedure to create a transparent rectangular box containing a model of the human airway for PIV measurement by combination of the RP and the curing of clear silicone. We extend this to make a whole airway including nasal cavities, larynx, trachea, and 2 generations of bronchi. The CBC algorithm with window offset (64 $\times$ 64 to 32 $\times$ 32) is used for vector searching in PIV analysis. The phase averaged mean and RMS velocity distributions in Sagittal and coronal planes are obtained for 7 phases in a respiratory period. Some physiologic conjectures are obtained. The main stream went through the backside of larynx and trachea in inspiration and the frontal side in expiration. There exist vortical motions in inspiration, but no prominent one in expiration.

• Childhood Kidney Diseases
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• v.17 no.1
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• pp.25-28
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• 2013

There have only been 35 pediatric cases and one adult case reported on segmental multicystic dysplastic kidney (MCDK) from our search in PubMed, including 19 cases detected antenatally. There is little documentation of segmental MCDK, particularly concerning its natural history. Segmental MCDK can be presented atypically, making diagnosis more difficult. We report an another case with segmental MCDK. Multicystic abdominal mass detected on antenatal sonogram in this infant was diagnosed as segmental MCDK by renal ultrasonography and computed tomography. If a definitive diagnosis of segmental MCDK can be made on imaging, surgery is not required for a diagnostic biopsy.

• Journal of Chest Surgery
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• v.37 no.2
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• pp.173-175
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• 2004

Primary pulmonary arterial sarcomas, especially those originating from the pulmonary valve are extremely rare. A 35 year-old male patient was admitted for exertional dyspnea and fatigue. Large intraluminal mass in the main pulmonary artery and both pulmonary arteries was detected by chest computed tomogram, chest magnetic resonance imaging, echocardiogram, and pulmonary angiogram. We regarded the mass as a primary pulmonary arterial malignant tumor, and resected under cardiopulmonary bypass. The mass was appeared to originate from the posterior cusp of pulmonary valve, and extended from below pulmonary valve to main pulmonary artery and both pulmonary arteries. We resected the mass by pulmonary endarterectomy and replaced the pulmonary valve. The mass was diagnosed as a pulmonary arterial sarcoma in histopathologic examination.

• Journal of Chest Surgery
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• v.38 no.6 s.251
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• pp.454-456
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• 2005

A 34-year-old male was admitted to our hospital complaining of chest pain. Chest computerized tomography showed pleural effusion and mass in left lower area. After open thoracotomy and mass removal originating from the parietal pleura were done. The mass was pathologically diagnosed as poorly differentiated synovial sarcoma. Synovial sarcoma of the pleura is rare. Herein we report a case of synovial sarcoma of the parietal pleura.

• Journal of Chest Surgery
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• v.40 no.9
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• pp.641-644
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• 2007

A 50-year old man was admitted to our hospital because he complained of sudden abdominal pain. Multidetector abdominal CT showed proximal occlusion of the superior mesenteric artery. Emergency open laparotomy and Fogarty thrombectomy were done on admission day and repeat Fogarty thrombectomy and partial resection of the small bowel were done the next day. We report here on a case of superior mesenteric artery occlusion.

• Korean Journal of Bronchoesophagology
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• v.4 no.1
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• pp.43-51
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• 1998

Background： Three-dementional imaging with spiral CT(3D spiral CT) is a well established imaging modality which has been investigated in various clinical settings. However the 3D spiral CT in upper airway disease is rarely reported and its results are still obscure. Objectives： To access the usefulness of 3D spiral CT imaging in patients with upper airway diseases. Materials and Methods We performed 3D spiral CT in fourteen patients In whom upper airway diseases were clinically suspected. Nine of these patients had upper airway stenosis, two had laryngeal cartilage fracture, and three had laryngo-hypopharyngeal cancer. For evaluation of location and extent of the lesions, we compared the findings of 3D imaging with those of air tracheogram, conventional 2D CT images, endoscopic and operative findings. Results： In case of stenosis, 3D spiral CT provide significant useful information, particularly the site and length of the stenotic segment. But, it was difficult to define the fracture of the laryngeal framework and to detect the cartilagenous invasion by head and neck cancer using the 3D imaging. Conclusion : The 3D spiral CT was an useful adjunctive method to assess some kind of upper airway disease but not in others. So, we should compare the findings of 3D images with those of other diagnostic tools for accurate diagnosis of the upper airway disease.

• Journal of the Korean Orthopaedic Association
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• v.55 no.5
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• pp.431-435
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• 2020

Pseudoaneurysm which is usually caused by high energy trauma or penetrating injury results in serious complications if the diagnosis is delayed. The authors experienced a 63-year-old patient who slipped on the stairs with simple contusion and skin laceration. But, he was finally diagnosed with pseudoaneurysm of tibioperoneal trunk of tibial artery on magnetic resonance imaging and 3-dimensional computed tomography angiogram performed in two weeks due to aggravation of the symptoms. To the best of my knowledge, pseudoaneurysm of tibio-peroneal trunk caused by minor blunt trauma has not been reported till now in Korea. So we report this case with a review of the relevant literature.

• Journal of the Korean Society of Radiology
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• v.18 no.3
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• pp.187-201
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• 2024

Osteoporosis is a major health issue globally, often remaining undetected until a fracture occurs. To facilitate early detection, deep learning (DL) models were developed to classify osteoporosis using abdominal computed tomography (CT) scans. This study was conducted using retrospectively collected data from 3,012 contrast-enhanced abdominal CT scans. The DL models developed in this study were constructed for using image data, demographic/clinical information, and multi-modality data, respectively. Patients were categorized into the normal, osteopenia, and osteoporosis groups based on their T-scores, obtained from dual-energy X-ray absorptiometry, into normal, osteopenia, and osteoporosis groups. The models showed high accuracy and effectiveness, with the combined data model performing the best, achieving an area under the receiver operating characteristic curve of 0.94 and an accuracy of 0.80. The image-based model also performed well, while the demographic data model had lower accuracy and effectiveness. In addition, the DL model was interpreted by gradient-weighted class activation mapping (Grad-CAM) to highlight clinically relevant features in the images, revealing the femoral neck as a common site for fractures. The study shows that DL can accurately identify osteoporosis stages from clinical data, indicating the potential of abdominal CT scans in early osteoporosis detection and reducing fracture risks with prompt treatment.

• Journal of the Korean Society of Radiology
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• v.12 no.6
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• pp.793-799
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• 2018

As interest in artificial intelligence has increased, artificial intelligence has been actively studied in the medical field. In Korea, artificial intelligence has been applied to medical imaging devices such as X-ray imaging, Computer Tomography and Magnetic Resonance Imaging and artificial intelligence capable of acquiring radiation images of patients without radiologists in the future Medical devices are expected to be invented. This study was an initial study on the automation of patient positioning in X - ray imaging. We used x-ray equipment and human phantoms to evaluate the positioning. The program used Visual Studio 2010 MFC and the image was in the size $1450{\times}1814$. The pixel values were converted to contrasts with values of 0 to 255 that can be visually recognized and output to the monitor. We developed a procedure algorithm program that predicts the angle of the output image through three pixel coordinate values and induces the patient to perform correct positioning according to the voice guidance according to the angle. In the next study, we will study the artificial intelligence to grasp the structure itself and calculate the angle, rather than conveying the reference of coordinates to artificial intelligence. In the future, it is expected that it will be helpful in the study of artificial intelligence from shooting to positioning through the automation of positioning.

• Journal of Dental Rehabilitation and Applied Science
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• v.25 no.2
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• pp.171-181
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• 2009

The objective of this study was to analyse stress distribution of maxillary complex by use of face mask. The construction of the three-dimensional FEM model was based on the computed tomography(CT) scans of 13.5 years-old male subject. The CT image were digitized and converted to the finite element model by using the mimics program, with PATRAN. An anteriorly directed force of 500g was applied at the first premolar 45 degrees downwards to the FH plane and at the first molar 20 degrees downwards to the FH plane. When 45 degrees force was applied at maxillary first premolar, there were observed expansion at molar part and constriction at premolar part. The largest displacement was 0.00011mm in the x-axis. In the y-axis, anterior displacement observed generally 0.00030mm at maximum. In the z-axis, maxillary complex was displaced 0.00036 mm forward and downward. When 20 degrees force was applied at maxilla first molar, there were observed expansion at lateral nasal wall and constriction at molar part. The largest displacement was 0.001mm in the X-axis. In the Y-axis, anterior displacement observed generally 0.004mm at maximum. In the Z-axis, ANS was displaced upward and pterygoid complex was displaced downward. The largest displacement was 0.002mm.