• 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.

• Nuclear Engineering and Technology
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• v.51 no.5
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• pp.1436-1443
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• 2019

A fast gamma-ray dose rate assessment method for complex geometries based on stylized model reconstruction and point-kernel method is proposed in this paper. The complex three-dimensional (3D) geometries are imported as a 3DS format file from 3dsMax software with material and radiometric attributes. Based on 3D stylized model reconstruction of solid mesh, the 3D-geometrical solids are automatically converted into stylized models. In point-kernel calculation, the stylized source models are divided into point kernels and the mean free paths (mfp) are calculated by the intersections between shield stylized models and tracing ray. Compared with MCNP, the proposed method can implement complex 3D geometries visually, and the dose rate calculation is accurate and fast.

• Journal of the Korean Society of Radiology
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• v.17 no.1
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• pp.37-46
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• 2023

This study aims to evaluate the usefulness of Deep Learning Image Reconstruction (TrueFidelity, TF), the image quality of existing Filtered Back Projection (FBP) and Adaptive Statistical Iterative Reconstruction-Veo (ASIR-V) were compared. Noise, CNR, and SSIM were measured by obtaining images with doses fixed at 17.29 mGy and altered to 10.37 mGy, 12.10 mGy, 13.83 mGy, and 15.56 mGy in reconstruction techniques of FBP, ASIR-V 50%, and TF-H. TF-H has superior image quality compared to FBP and ASIR-V when the reconstruction technique change is given at 17.29 mGy. When dose changes were made, Noise, CNR, and SSIM were significantly different when comparing 10.37 mGy TF-H and FBP (p<0.05), and no significant difference when comparing 10.37 mGy TF-H and ASIR-V 50% (p>0.05). TF-H has a dose-reduction effect of 30%, as the highest dose of 15.56 mGy ASIR-V has the same image quality as the lowest dose of 10.37 mGy TF-H. Thus, Deep Learning Reconstruction techniques (TF) were able to reduce dose compared to Iterative Reconstruction techniques (ASIR-V) and Filtered Back Projection (FBP). Therefore, it is considered to reduce the exposure dose of patients.

• Progress in Medical Physics
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• v.28 no.1
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• pp.27-32
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• 2017

We investigated the effect of a commercial iterative reconstruction technique (iDose, Philips) on the image quality and the dose calculation for the treatment plan. Using the electron density phantom, the 3D CT images with five different protocols (50, 100, 200, 350 and 400 mAs) were obtained. Additionally, the acquired data was reconstructed using the iDose with level 5. A lung phantom was used to acquire the 4D CT with the default protocol as a reference and the low dose (one third of the default protocol) 4D CT using the iDose for the spine and lung plans. When applying the iDose at the same mAs, the mean HU value was changed up to 85 HU. Although the 1 SD was increased with reducing the CT dose, it was decreased up to 4 HU due to the use of iDose. When using the low dose 4D CT with iDose, the dose change relative to the reference was less than 0.5% for the target and OARs in the spine plan. It was also less than 1.1% in the lung plan. Therefore, our results suggests that this dose reduction technique is applicable to the 4D CT image acquisition for the radiation treatment planning.

• The Korean Journal of Food & Health Convergence
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• v.4 no.1
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• pp.23-31
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• 2018

The main issue of CT is radiation dose reduction to patient. The purpose of this study was to estimate the image quality and dose by iterative reconstruction (IR) for adults and pediatrics. Adult and pediatric images of phantom were obtained with 120 and 140 kV, respectively, in accordance with radiation dose in terms of volume CT dose index ($CTDI_{vol}$): 10, 15, 20, 25, 30, 35 mGy. Then, the adult and the pediatric images are reconstructed by filtered-backprojection (FBP) and iterative reconstruction (IR). The images were analyzed by signal-to-noise ratio (SNR). SNR is improved when IR and 140 kV are applied to acquire adult and pediatric images. In the adult abdomen, according to diagnostic reference level, the SNR values of bone were increased about 27.84 % and 27.77 % at 120 kV and 140 kV, and the tissue's SNR values of the IR were increased about 29.84 % and 33.46 % 120 and 140 kV, respectively. Dose is reduced to 40% in adults abdomen images when using IR reconstruction. In pediatric images, the bone's SNR were also increased about 17.70% and 18.17 % at 120 kV and 140 kV. The tissue's SNR were increased about 26.73 % and 26.15 % at 120 kV and 140 kV. Radiation dose is reduced from 30% to 50% for bone and tissue images. In the case of examinations for adult and pediatric CT, IR technique reduces radiation dose to patient, and it could be applied to adult and pediatric imaging.

• Korean Journal of Radiology
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• v.23 no.4
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• pp.402-412
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• 2022

Objective: To evaluate the image quality and lesion detectability of lower-dose CT (LDCT) of the abdomen and pelvis obtained using a deep learning image reconstruction (DLIR) algorithm compared with those of standard-dose CT (SDCT) images. Materials and Methods: This retrospective study included 123 patients (mean age ± standard deviation, 63 ± 11 years; male:female, 70:53) who underwent contrast-enhanced abdominopelvic LDCT between May and August 2020 and had prior SDCT obtained using the same CT scanner within a year. LDCT images were reconstructed with hybrid iterative reconstruction (h-IR) and DLIR at medium and high strengths (DLIR-M and DLIR-H), while SDCT images were reconstructed with h-IR. For quantitative image quality analysis, image noise, signal-to-noise ratio, and contrast-to-noise ratio were measured in the liver, muscle, and aorta. Among the three different LDCT reconstruction algorithms, the one showing the smallest difference in quantitative parameters from those of SDCT images was selected for qualitative image quality analysis and lesion detectability evaluation. For qualitative analysis, overall image quality, image noise, image sharpness, image texture, and lesion conspicuity were graded using a 5-point scale by two radiologists. Observer performance in focal liver lesion detection was evaluated by comparing the jackknife free-response receiver operating characteristic figures-of-merit (FOM). Results: LDCT (35.1% dose reduction compared with SDCT) images obtained using DLIR-M showed similar quantitative measures to those of SDCT with h-IR images. All qualitative parameters of LDCT with DLIR-M images but image texture were similar to or significantly better than those of SDCT with h-IR images. The lesion detectability on LDCT with DLIR-M images was not significantly different from that of SDCT with h-IR images (reader-averaged FOM, 0.887 vs. 0.874, respectively; p = 0.581). Conclusion: Overall image quality and detectability of focal liver lesions is preserved in contrast-enhanced abdominopelvic LDCT obtained with DLIR-M relative to those in SDCT with h-IR.

• Progress in Medical Physics
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• v.11 no.2
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• pp.91-99
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• 2000

This is a preliminary study for developing the method of the dose reconstruction in the patients, irradiated by mega-voltage photon beams from the linear accelerator, using the transit dose distributions. In this study we present the method of three-dimensional dose reconstruction and evaluate the method by computer simulation. To acquire the dose distributions in the patients (or phantoms) we first calculate the differences between the doses at the arbitrary points in the patients and the doses at the corresponding points where the transit doses are measured. Then, we can get the dose in the patients from the measured transit dose and the calculated value of the difference. The dose differences are calculated by applying the inverse square law and using the linear attenuation coefficient. The scatter to primary dose ratios, which are calculated by the Monte Carlo program using the CT data of the patient (or phantoms), are also used in the calculations. For the evaluation of this method we used various kinds of homogeneous and inhomogeneous phantoms and calculated the transit dose distributions with the Monte Carlo program. From the distributions we reconstructed the dose distributions in the phantom. We used mono-energy Photon beam of 1.5MeV and Monte Carlo program EGS4. The comparison between the dose distributions reconstructed using the method and the distributions calculated by the Monte Carlo program was done. They agreed within errors of -4%∼+2%. This method can be used to predict the dose distributions in the patient

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.9
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• pp.143-147
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• 2016

Recently, digital tomosynthesis system (DTS) has been developed to reduce overlap using conventional X-ray and to overcome high patient dose problem using computed tomography (CT). The purpose of this study was to develop image reconstruction algorithm and to evaluate image characteristics and dose with chest digital tomosynthesis (CDT) system. Image reconstruction was used for filtered back-projection (FBP) methods and system geometry was constructed ${\pm}10^{\circ}$, ${\pm}15^{\circ}$, ${\pm}20^{\circ}$, and ${\pm}30^{\circ}$ angular range for acquiring phantom images. Image characteristics carried out root mean square error (RMSE) and signal difference-to-noise ratio (SDNR), and dose is evaluated effective dose with ${\pm}20^{\circ}$ angular range. According to the results, the phantom image with slice thickness filter has superb RMSE and SDNR, and effective dose was 0.166 mSv. In conclusion, we demonstrated usefulness of developed CDT image reconstruction algorithm and we constructed CDT basic output data with measuring effective dose.

• Journal of the Korean Society of Radiology
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• v.17 no.7
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• pp.1025-1031
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• 2023

We aimed to evaluate the radiation dose and image quality by changing the Scout view voltage in low-dose chest CT (LDCT) and applying scan parameters such as AEC (auto exposure control) and ASIR (adaptive statistical iterative reconstruction) to find the optimal protocol. Scout view voltage was varied at 80, 100, 120, 140 kV and after measuring the dose 5 times using the existing low-dose chest CT protocol, the appropriate kV was selected for the study using the Dose report provided by the equipment. After taking a basic LDCT shot at 120 kV, 30 mAs, ASIR 50% was applied to this condition. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed by measuring Background noise (B/N). For dose comparison, CTDI_vol and DLP provided by the equipment were compared and analyzed using the formulas. The results indicated that the protocol of scout 140 + LDCT + ASIR 50 + AEC reduced radiation exposure and improved image quality compared to traditional LDCT, providing an optimal protocol. As demonstrated in the experiment, LDCT screenings for asymptomatic normal individuals are crucial, as they involve concerns over excessive radiation exposure per examination. Therefore, applying appropriate parameters is important, and it is expected to contribute positively to the public health in future LDCT based health screenings.

• Archives of Plastic Surgery
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• v.44 no.6
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• pp.509-515
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• 2017

Background Skin flap necrosis is a common complication after mastectomy and breast reconstruction. It has been proven that nitroglycerin ointment, as a topical vasodilator, can decrease the rate of skin flap necrosis after mastectomy and breast reconstruction. However, nitroglycerin can cause several side effects, including headache, dizziness, and hypotension. The purpose of this study was to evaluate whether the application of a low dose of nitroglycerin ointment reduced the rate of skin flap necrosis in breast reconstruction after skin-sparing or nipple-sparing mastectomy. Methods A total of 73 cases of breast reconstruction after nipple-sparing and skin-sparing mastectomy at our institution from March 2012 to January 2017 were retrospectively studied. Of these patients, 52 received nitroglycerin ointment (4.5 mg) application to the skin around the nipple-areolar complex from August 2015 to January 2017, while 21 received fusidic acid ointment from March 2012 to August 2015. The number of patients who experienced necrosis of the breast skin flap was counted in both groups. Results Skin flap necrosis developed in 2 (3.8%) patients who were treated with nitroglycerin ointment and 5 (23.8%) patients who did not receive nitroglycerin ointment treatment. Patients who did not receive nitroglycerin ointment treatment had a significantly higher risk of mastectomy skin flap necrosis than patients who did (odds ratio=7.81; 95% confidence interval, 1.38 to 44.23; P=0.02). Conclusions Low-dose nitroglycerin ointment administration significantly decreased the rate of skin flap necrosis in patients who underwent breast reconstruction after skin-sparing or nipple-sparing mastectomy, without increasing the incidence of the side effects of nitroglycerin.