• Journal of Digital Convergence
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• v.16 no.2
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• pp.19-26
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• 2018

We proposed a numerical calculation of the proportion of necrotic cells in pulmonary segmentation, pulmonary vessel segmentation lung disease site for diagnosis of lung disease from chest CT images. The first step is to separate the lungs and bronchi by applying a three-dimensional labeling technique from a chest CT image and a three-dimensional region growing method. The second step is to divide the pulmonary vessels by applying the rate of change using the first order polynomial regression, perform noise reduction, and divide the final pulmonary vessels. The third step is to find a disease prediction factor in a two-step image and calculate the proportion of necrotic cells.

• Journal of the Korean Society of Radiology
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• v.81 no.3
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• pp.591-603
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• 2020

Purpose The purpose of this study was to describe the clinical features and chest computed tomography (CT) findings of coronavirus disease 2019 (COVID-19) pneumonia. Materials and Methods An Institutional Review Board-approved retrospective review was performed for 51 laboratory-confirmed COVID-19 pneumonia patients. Patients were divided into two groups depending on their clinical status: mild and severe. Clinical characteristics and chest CT findings were compared between the two groups. Results Among the 51 patients (22 men, 29 women; mean age, 56.5 ± 16 years; range, 22-88 years), 37 (72.5%) were in the mild group and 14 (27.5%) were in the severe group. The patients in the severe group (68.7 ± 12.5 years) were older than the patients in the mild group (51.8 ± 14.9 years, p < 0.001). Premorbid conditions and decreased lymphocyte counts were more often observed in the severe group than in the mild group (71% vs. 41%, p = 0.049 and 86% vs. 32%, p = 0.001, respectively). On chest CT, most patients exhibited a mixed ground-glass opacification (GGO) with consolidation (76%) or a GGO (22%) pattern. The majority of lesions were predominantly bilateral in the lower lung with a posterior, peripheral distribution. The patients in the severe group had higher severity scores than those in the mild group. Conclusion Patients with laboratory-confirmed COVID-19 pneumonia have typical chest CT findings that provide important information regarding expected disease severity.

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.159-168
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• 2019

We examined the effect of Siemens ADMIRE (Advanced Modeled Iterative Reconstruction) on image quality by measuring changes in HU, noise, and SNR of background air, fat, muscle, and background signals on a chest CT scan. Experimental results show that as the ADMIRE Strength increases, the noise decreases and the signal increases, consequently the signal-to-noise ratio increases. ADMIRE can reduce noise by 28 ~ 61% compared to FBP, which is a conventional image reconstruction algorithm, and improves SNR by 16 ~ 100%.

• Journal of the Korean Society of Radiology
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• v.84 no.6
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• pp.1337-1338
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• 2023

• Journal of the Korea Computer Graphics Society
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• v.24 no.5
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• pp.31-39
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• 2018

In this paper, we propose an automated method for the ground-glass nodule(GGN) classification using GGN-Net based on intensity, texture, and shape-enhanced images in chest CT images. First, we propose the utilization of image that enhances the intensity, texture, and shape information so that the input image includes the presence and size information of the solid component in GGN. Second, we propose GGN-Net which integrates and trains feature maps obtained from various input images through multiple convolution modules on the internal network. To evaluate the classification accuracy of the proposed method, we used 90 pure GGNs, 38 part-solid GGNs less than 5mm with solid component, and 23 part-solid GGNs larger than 5mm with solid component. To evaluate the effect of input image, various input image set is composed and classification results were compared. The results showed that the proposed method using the composition of intensity, texture and shape-enhanced images showed the best result with 82.75% accuracy.

• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.297-303
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• 2023

Pediatric Computed Tomography (CT) examinations can often result in exam failures or the need for frequent retests due to the difficulty of cooperation from young patients. Deep Learning Image Reconstruction (DLIR) methods offer the potential to obtain diagnostically valuable images while reducing the retest rate in CT examinations of pediatric patients with high radiation sensitivity. In this study, we investigated the possibility of applying DLIR to reduce artifacts caused by respiration or motion and obtain clinically useful images in pediatric chest CT examinations. Retrospective analysis was conducted on chest CT examination data of 43 children under the age of 7 from P Hospital in Gyeongsangnam-do. The images reconstructed using Filtered Back Projection (FBP), Adaptive Statistical Iterative Reconstruction (ASIR-50), and the deep learning algorithm TrueFidelity-Middle (TF-M) were compared. Regions of interest (ROI) were drawn on the right ascending aorta (AA) and back muscle (BM) in contrast-enhanced chest images, and noise (standard deviation, SD) was measured using Hounsfield units (HU) in each image. Statistical analysis was performed using SPSS (ver. 22.0), analyzing the mean values of the three measurements with one-way analysis of variance (ANOVA). The results showed that the SD values for AA were FBP=25.65±3.75, ASIR-50=19.08±3.93, and TF-M=17.05±4.45 (F=66.72, p=0.00), while the SD values for BM were FBP=26.64±3.81, ASIR-50=19.19±3.37, and TF-M=19.87±4.25 (F=49.54, p=0.00). Post-hoc tests revealed significant differences among the three groups. DLIR using TF-M demonstrated significantly lower noise values compared to conventional reconstruction methods. Therefore, the application of the deep learning algorithm TrueFidelity-Middle (TF-M) is expected to be clinically valuable in pediatric chest CT examinations by reducing the degradation of image quality caused by respiration or motion.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.3-7
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• 2010

Purpose: The usefulness of Positron Emission Tomography (PET) images in diagnosis, staging, recurrent and treatment response evaluation has already been known. However, tumors which are small size, located in lower lobe of lung or upper lobe of liver are shown misalignment, distortion and different Standard Uptake Value (SUV) by respiration in PET images. Therefore, if radiotherapy based on normal respiration, it may cause low treatment response or more side effects because targets which had to treat, out of treat range or over dose to normal tissue. The purpose of this study is to evaluate attenuation-correction with Average CT (ACT) for more accuracy SUV measurement and minimize artifact by respiration. Materials and Methods: 13 patients, who had tumors which are around the diaphragm, underwent ACT scan after Helical CT (HCT) scan with PET/CT (Discovery DSTE 8; GE Healthcare). We quantified the differences between attenuation corrected image with HCT and attenuation corrected image with ACT in artifact size and maximum SUV ($SUV_{max}$). Artifacts were evaluated by measurement of the curved photogenic area in the lower thorax of the PET images for all patients. $SUV_{max}$ was measured separately at the primary tumors. Analysis program was Advantage Workstation v4.3 (GE Healthcare). Patients were injected with 7.4 MBq (0.2 $mC_i$) per kg of $^{18}F$-FDG and scanned 1 hour after injection. The PET acquisition was 3 minute per bed. Results: Significantly lower artifact were observed in PET/ACT images than in PET/HCT images (below-thoracic artifacts caused by under corrected $1.5{\pm}3.5$ cm vs. $13.4{\pm}4.2$ cm). Significantly higher $SUV_{max}$ were noted in PET/ACT images than in PET/HCT images in the primary tumor. Compared with PET/HCT images, $SUV_{max}$ in PET/ACT images were higher by $5.3{\pm}3.9%$ (mean value) tumor. The highest difference was observed in Lower lobe of lung (7.7 to 8.7; 13%). Conclusion: Due to its significantly reduced artifacts in lower thoracic, attenuation corrected image with ACT images provided more reliable $SUV_{max}$ and may be helpful in monitoring treatment response. Moreover, ACT can separate upper lobe of liver and lower lobe of lung, it may be helpful in interpretation. ACT will be clinically useful, considering increased dose caused by ACT scan and adapt.

• Journal of the Korean Society of Radiology
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• v.82 no.3
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• pp.756-763
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• 2021

Pulmonary Langerhans cell histiocytosis (PLCH) is a rare, multi-systemic disease primarily affecting young male adults with a history of smoking. The two patients with PLCH in our report showed relatively early and atypical radiologic presentations at initial evaluation. On chest CT, PLCH presents variable radiologic features depending on the evolutional stage of the disease. Atypical CT features of PLCH may render precise radiologic diagnosis difficult and usually require lung biopsy for a confirmation of the diagnosis. Our case review is aimed at raising the awareness of radiologists on the atypical CT features of PLCH, to help make accurate radiologic diagnosis and prevent unnecessary and invasive diagnostic procedures.

• The Journal of the Korea Contents Association
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• v.19 no.8
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• pp.284-292
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• 2019

To evaluate the usefulness of pediatric chest CT scans by comparing the dose, examination time, and image quality by applying Helical mode, High-pitch mode, and Volume Axial mode to minimize the radiation exposure and obtain high diagnostic value. Revolution (GE Healthcare, Wisconsin USA) was used to divide PBU-70 phantom into Helical mode, High-pitch mode, and Volume Axial mode. After acquiring images, ROI is set for each image, heart, bone, lung, and back-ground air, and the average value is obtained by measuring CT number (HU) and noise (SD). SNR and CNR were measured and compared with DLP values provided directly by the equipment. Determining statistical significance Statistical analysis was performed using ONE-WAY-ANAOVA using SPSS 21.0. In this experiment, it was possible to inspect at a short time without deterioration of image quality with the lowest dose when using volume axial mode. Although the detector coverage of 16 cm is limited to all pediatric chest CT scans, it is recommended to be actively used in pediatric patients, and further study is needed to apply other test sites in volume axial mode.

• Journal of the Korean Society of Radiology
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• v.84 no.5
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• pp.1191-1196
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• 2023

Bronchial artery aneurysm (BAA) is a rare disease, and multiple aneurysms of a single bronchial artery are rarer. Regardless of the size of the lesion, it is at risk of rupture and can cause massive hemoptysis or severe pain. We report a rare case of bronchial artery embolization (BAE) of multiple aneurysms of a single bronchial artery. During medical examination, a 64-year-old female was diagnosed with multiple BAAs and endobronchial lesions in the right lower lung on CT 10 years prior to presentation to our hospital. Further evaluation of the lesions was recommended; however, the patient was lost to follow-up. The patient complained of dyspnea and visited our hospital, and the size of the BAA had increased on CT. BAE was done successfully using N-butyl-2-cyanoacrylate and detachable coils. Follow up CT after BAE showed significant decrease in extent of inflammatory lesion in the right lung.