• Journal of Korea Multimedia Society
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• v.20 no.6
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• pp.865-872
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• 2017

Recent advance in electronics and scintillators makes it possible to utilize the time-of-flight (TOF) information in improving image reconstruction of positron emission tomography(PET). In this paper, we propose a TOF-based fast image reconstruction method for PET. The proposed method uses the deconvolution of TOF data for each angle view and the rotational averaging of deconvolved images. Simulation results show an improved performance of the proposed method, as compared with filtered backprojection (FBP) method, TOF-FBP, and TOF version of expectation-maximization(EM) methods. Simulation results also show a great potentiality of the proposed method in limited angle tomography applications.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10b
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• pp.977-982
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• 2000

As a newly structural system, RCS composite system has been researched last two decades. However mechanism of exterior T-type joint for RCS composite system is not well known. This research is focus on the exterior T-type joint for RCS composite system. Specimens are designed by the ASCE guideline, tested and compared with the inner RCS joint. Test variables include face bearing plate(FBP), extended face bearing plate(E-FBP) and U-bar. The tests indicate that the strength of exterior T-type joint is higher than that of the guideline by ASCE. The U-bar has a significant effect on the joint strength and absorbing the strain energy.

• Korean Journal of Artificial Intelligence
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• v.9 no.2
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• pp.1-5
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• 2021

Although CT has an advantage in describing the three-dimensional anatomical structure of the human body, it also has a disadvantage in that high doses are exposed to the patient. Recently, a deep learning-based image reconstruction method has been used to reduce patient dose. The purpose of this study is to analyze the dose reduction and image quality improvement of deep learning-based reconstruction (DLR) on the adult's chest CT examination. Adult lung phantom was used for image acquisition and analysis. Lung phantom was scanned at ultra-low-dose (ULD), low-dose (LD), and standard dose (SD) modes, and images were reconstructed using FBP (Filtered back projection), IR (Iterative reconstruction), DLR (Deep learning reconstruction) algorithms. Image quality variations with respect to varying imaging doses were evaluated using noise and SNR. At ULD mode, the noise of the DLR image was reduced by 62.42% compared to the FBP image, and at SD mode, the SNR of the DLR image was increased by 159.60% compared to the SNR of the FBP image. Based on this study, it is anticipated that the DLR will not only substantially reduce the chest CT dose but also drastic improvement of the image quality.

• Korean Journal of Radiology
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• v.23 no.7
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• pp.752-762
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• 2022

Objective: To compare a deep learning-based reconstruction (DLR) algorithm for pediatric abdominopelvic computed tomography (CT) with filtered back projection (FBP) and iterative reconstruction (IR) algorithms. Materials and Methods: Post-contrast abdominopelvic CT scans obtained from 120 pediatric patients (mean age ± standard deviation, 8.7 ± 5.2 years; 60 males) between May 2020 and October 2020 were evaluated in this retrospective study. Images were reconstructed using FBP, a hybrid IR algorithm (ASiR-V) with blending factors of 50% and 100% (AV50 and AV100, respectively), and a DLR algorithm (TrueFidelity) with three strength levels (low, medium, and high). Noise power spectrum (NPS) and edge rise distance (ERD) were used to evaluate noise characteristics and spatial resolution, respectively. Image noise, edge definition, overall image quality, lesion detectability and conspicuity, and artifacts were qualitatively scored by two pediatric radiologists, and the scores of the two reviewers were averaged. A repeated-measures analysis of variance followed by the Bonferroni post-hoc test was used to compare NPS and ERD among the six reconstruction methods. The Friedman rank sum test followed by the Nemenyi-Wilcoxon-Wilcox all-pairs test was used to compare the results of the qualitative visual analysis among the six reconstruction methods. Results: The NPS noise magnitude of AV100 was significantly lower than that of the DLR, whereas the NPS peak of AV100 was significantly higher than that of the high- and medium-strength DLR (p < 0.001). The NPS average spatial frequencies were higher for DLR than for ASiR-V (p < 0.001). ERD was shorter with DLR than with ASiR-V and FBP (p < 0.001). Qualitative visual analysis revealed better overall image quality with high-strength DLR than with ASiR-V (p < 0.001). Conclusion: For pediatric abdominopelvic CT, the DLR algorithm may provide improved noise characteristics and better spatial resolution than the hybrid IR algorithm.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.2
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• pp.30-35
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• 2011

Purpose: The Boramae Hospital are currently using Wide beam reconstruction (WBR: UltraSPECT, Israel) to improve the resolution. The Xact-bone belongs to the WBR. It has been reported that Xact-bone helps us to improve image resolution and contrast. This study will be evaluated clinical usefulness of Xact-bone method. Materials and Methods: The usefulness evaluation of Xact-bone method was analyzed in resolution test and contrast ratio. The resolution test in Planar image were obtained from Full width at half maximum (FWHM) by using capillary tube. And the contrast ratio was obtained from Bone and Soft tissue (B/S) ratio values that were acquired from bone scan study of 50 patients before and after using the Xact-bone method. We prepared the Triple Line Source Phantom, NEMA IEC Body Phantom and Standard Jaszczak Phantom to acquire the FWHM and Contrast Ratio values of Single photon emission computed tomography (SPECT) image. Subsequently we compared among the Filtered backprojection (FBP), Orderd subset expectation maximization (OSEM) and Xact-Bone image. Results: The results of the planar Xact-bone data improved resolution about 20% by using capillary tube. In addition it was improved B/S ratio about 15%. When using Triple Line Source Phantom, SPECT Xact-bone data improved resolution for both FBP, OSEM methods about 20% and 10%, respectively. Contrast ratio in each spheres has also been increased for both methods that using NEMA IEC body Phantom and Standard Jaszczak Phantom. Conclusion: When we were using Xact-bone method, we could see to improve the resolution and Contrast ratio as compared to do not use the Xact-bone method. Accordingly, by using WBR's Xact-bone method is expected to improve the image quality. However, when introducing new software, it is needed to match the characteristics of the hospital protocol and clinical application.

• 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.

• Journal of the Korean Society of Radiology
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• v.83 no.3
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• pp.669-679
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• 2022

Purpose To evaluate the feasibility of pediatric low-dose facial CT reconstructed with filtered back projection (FBP) using adequate kernels. Materials and Methods We retrospectively reviewed the clinical and imaging data of children aged < 10 years who underwent facial CT at our emergency department. The patients were divided into two groups: low-dose CT (LDCT; Group A, n = 73) with a fixed 80-kVp tube potential and automatic tube current modulation (ATCM) and standard-dose CT (SDCT; Group B, n = 40) with a fixed 120-kVp tube potential and ATCM. All images were reconstructed with FBP using bone and soft tissue kernels in Group A and only bone kernel in Group B. The groups were compared in terms of image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Two radiologists subjectively scored the overall image quality of bony and soft tissue structures. The CT dose index volume and dose-length product were recorded. Results Image noise was higher in Group A than in Group B in bone kernel images (p < 0.001). Group A using a soft tissue kernel showed the highest SNR and CNR for all soft tissue structures (all p < 0.001). In the qualitative analysis of bony structures, Group A scores were found to be similar to or higher than Group B scores on comparing bone kernel images. In the qualitative analysis of soft tissue structures, there was no significant difference between Group A using a soft tissue kernel and Group B using a bone kernel with a soft tissue window setting (p > 0.05). Group A showed a 76.9% reduction in radiation dose compared to Group B (3.2 ± 0.2 mGy vs. 13.9 ± 1.5 mGy; p < 0.001). Conclusion The addition of a soft tissue kernel image to conventional CT reconstructed with FBP enables the use of pediatric low-dose facial CT protocol while maintaining image quality.

• Journal of the Korean Society of Radiology
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• v.17 no.1
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• pp.1-9
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• 2023

For optimal image quality of computer tomography angiography (CTA), different iodine concentrations and scan parameters were applied to quantitatively evaluate the image quality characteristics of filtered back projection (FBP), hybrid-iterative reconstruction (hybrid-IR), and deep learning reconstruction (DLR). A 320-row-detector CT scanner scanned a phantom with various iodine concentrations (1.2, 2.9, 4.9, 6.9, 10.4, 14.3, 18.4, and 25.9 mg/mL) located at the edge of a cylindrical water phantom with a diameter of 19 cm. Data obtained using each reconstruction technique was analyzed through noise, coefficient of variation (COV), and root mean square error (RMSE). As the iodine concentration increased, the CT number value increased, but the noise change did not show any special characteristics. COV decreased with increasing iodine concentration for FBP, adaptive iterative dose reduction (AIDR) 3D, and advanced intelligent clear-IQ engine (AiCE) at various tube voltages and tube currents. In addition, when the iodine concentration was low, there was a slight difference in COV between the reconstitution techniques, but there was little difference as the iodine concentration increased. AiCE showed the characteristic that RMSE decreased as the iodine concentration increased but rather increased after a specific concentration (4.9 mg/mL). Therefore, the user will have to consider the characteristics of scan parameters such as tube current and tube voltage as well as iodine concentration according to the reconstruction technique for optimal CTA image acquisition.

• Proceedings of the Korea Contents Association Conference
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• 2014.11a
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• pp.191-192
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• 2014

두부 CT 검사 시 FBP와 ASIR적용에 따른 화질과 선량을 평가해 보고, Scan type(Axial, Helical)별 영상을 비교해 보아 두부 CT 영상획득 시 최적의 방법을 알아보고자 하였다.

• YAKHAK HOEJI
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• v.50 no.1
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• pp.52-57
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• 2006

The activation of cyclin dependent kinase 4 (CDK4) is found in more than half of all human cancers. Therefore CDK4 is an attractive target for the development of a novel anticancer agent. For mass screening of CDK4 inhibitor, we set up in vitro kinase assay for CDK4 activity using a cyclin D1-CDK4 fusion protein, which is constitutively active and exhibits enhanced stability. From the screening of representative compound library of Korea Chemical Bank, we found that 7-chloro-4-nitro-benzo[1,2,5]oxadiazole 1-oxide (FBP-1248) selectively inhibited CDK4 activity in vitro by ATP competitive manner. This compound prevented the phosphorylation of retinoblatsoma tumor suppressor protein, Rb, and inhibited cell growth through cell cycle arrest. In summary, we developed an efficient assay system for CDK4 activity in vitro and identified the CDK4 inhibitory compound, FBP-1248.