• 한국인공지능학회지
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• 제9권2호
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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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• 제51권5호
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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.

• 한국방사선학회논문지
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• 제17권1호
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• pp.37-46
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• 2023

MDCT의 딥러닝 재구성 기법(TrueFidelity, TF)의 유용성을 평가하고자 기존의 필터보정역투영법(Filtered back projection, FBP)과 적응형 통계적 재구성 기법(Adaptive Statistical Iterative Reconstruction-Veo, ASIR-V)의 화질을 비교 평가하였다. FBP, ASIR-V 50%, TF-H의 재구성 기법에서 선량을 17.29 mGy로 고정한 것과 10.37 mGy, 12.10 mGy, 13.83 mGy, 15.56 mGy로 변화시킨 영상을 획득하여 노이즈, CNR, SSIM을 측정하였다. 17.29 mGy에서 재구성 기법 변화를 주었을 때 TF-H가 FBP, ASIR-V에 비해 화질이 우수하다. 선량에 변화를 주었을 때 10.37 mGy TF-H와 FBP 비교 시 노이즈, CNR, SSIM은 유의한 차이가 있고(p<0.05), 10.37 mGy TF-H와 ASIR-V 50% 비교 시 유의한 차이가 없다(p>0.05). 선량이 가장 높은 15.56 mGy ASIR-V 50%와 선량이 가장 낮은 10.37 mGy TF-H 화질이 동일하므로 TF-H는 30%의 선량 감소 효과가 있다. 따라서 딥러닝 재구성 기법(TF)은 반복적 재구성 기법(ASIR-V)과 필터보정역투영법(FBP)보다 선량을 감소시킬 수 있었다. 이로 인해 환자의 피폭선량을 감소시킬 것으로 사료된다.

• 한국의학물리학회지:의학물리
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• 제28권1호
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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.

• 식품보건융합연구
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• 제4권1호
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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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• 제23권4호
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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.

• 한국의학물리학회지:의학물리
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• 제11권2호
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• pp.91-99
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• 2000

본 연구는 선형 가속기에서 나오는 고 에너지 광자빔 조사를 받은 환자 내부의 선량 분포를 조사문 선량 분포로부터 재구성하는 방법을 개발하기 위한 기초 연구로서 삼차원 선량 분포를 재구성하는 방법을 제시하고 이 방법을 전산모사를 통해 평가하였다. 본 연구에서 제안하는 방법은 환자나 팬톰 내부의 임의의 지점에서 흡수된 선량과 그 지점에 대응되는 조사문 선량의 측정 지점에서 흡수된 선량의 차이를 계산하여 측정된 조사문 선량 분포로부터 환자나 팬톰 내부의 선량분포를 얻는 것이다. 선량의 차이는 역제곱법칙과 선형감쇄계수, 그리고 Monte Carlo 프로그램을 이용하여 환자나 팬톰의 CT 정보로부터 계산한 산란선량과 주선량의 비(scatter to primary dose ratio)를 이용하여 계산한다. 이 방법을 시험하기 위해 여러 종류의 균질 혹은 비균질 팬톰의 조사문 선량 분포를 Monte Carlo 전산모사로 계산한 뒤 팬톰 내부의 선량 분포를 재구성하였다. 광자빔은 1.5 MeV의 단일에너지를 사용하였고 Monte Carlo 프로그램은 EGS4를사용하였다. 본 연구의 방법을 사용하여 재구성된 팬톰 내부의 선량 분포와 Monte Carlo로 계산한 팬텀 내부의 선량 분포와 비교하였다. 비교 결과 오차 -4%∼+2% 이내로 일치하였다. 이 방법은 다른 in vivo dosimetry 방법을 대신하여 환자내의 선량분포를 예측하는데 쓰여질 수 있을 것이다.

• 전자공학회논문지
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• 제53권9호
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• pp.143-147
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• 2016

최근 디지털 단층영상합성 시스템 (digital tomosynthesis system, DTS)은 일반 X-ray의 영상 중첩현상과 전산화단층촬영장치 (computed tomography, CT)의 높은 선량의 문제점을 해결하기 위하여 개발되었다. 본 연구의 목적은 흉부 촬영용 디지털 단층영상합성 시스템 (chest digital tomosynthesis, CDT)의 재구성 알고리즘 개발 및 화질과 선량 평가를 수행하는 것이다. 영상의 재구성은 필터 후 역투영 (filtered back-projection, FBP)을 모델링하였고, 팬텀 영상을 획득하기 위한 X-선과 검출기 사이의 각도를 ${\pm}10^{\circ}$, ${\pm}15^{\circ}$, ${\pm}20^{\circ}$, 그리고 ${\pm}30^{\circ}$로 구성하였다. 영상의 화질 평가는 평균 제곱근 편차 (root mean square error, RMSE)와 신호대 잡음 변화율 (signal difference-to-noise ratio, SDNR)로 수행하였고, 선량 평가는 ${\pm}20^{\circ}$의 범위에서 유효선량으로 수행하였다. 결과적으로, 모든 각도에서 Slice thickness 필터를 적용한 팬텀영상이 가장 우수한 RMSE와 SDNR 결과를 나타내었고, 최종 유효 선량은 0.166 mSv로 측정되었다. 결론적으로, 개발한 CDT 재구성 알고리즘의 유용성을 증명하였고, 최종 유효 선량을 측정하여 CDT의 기초 실험 데이터를 구축할 수 있었다.

• 한국방사선학회논문지
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• 제17권7호
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• pp.1025-1031
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• 2023

저선량흉부 CT (Low Dose chest CT, LDCT)에서 Scout 관전압을 변화시키고 scan parameter인 자동노출제어장치(Auto Exposure Control, AEC)와 적응식 반복재구성기법(Adaptive Statistical Iterative Reconstruction, ASIR)등을 적용하여 최적의 프로토콜을 찾음으로써 방사선 피폭선량과 화질을 평가하고자 하였다. Scout 관전압을 80, 100, 120, 140 kV로 변화시키며 LDCT 프로토콜로 5회 반복 측정 후 선량을 비교하기 위해 장비에서 제공된 Dose report를 이용하여 연구 목적에 적합한 관전압을 선택하였다. 120 kV, 30 mAs의 조건으로 기본 LDCT 촬영한 후, 이 조건에 ASIR 50%를 적용하였으며 신호대잡음비와 대조도대잡음비를 평가하기 위해 배경의 노이즈를 측정하였다. 선량 비교를 위해 장비에서 제공되는 CTDI_vol과 선량길이곱(Dose length product, DLP)를 식을 이용하여 비교 분석하였다. 그 결과 S140 + LDCT + ASIR 50 + AEC를 적용한 프로토콜에서 고식적인 LCDT보다 방사선 피폭선량을 감소시키고 영상의 질을 향상시켰으며 최적의 프로토콜을 얻을 수 있었으며 LDCT는 매 검사 시 필요 이상의 피폭선량이 우려되기 때문에 적절한 Parameter를 적용하는 것이 중요하며, 향후 LDCT를 이용한 건강검진에서 국민의 건강에 이바지 하는데 긍정적인 요인으로 작용될 것으로 사료된다.

• Archives of Plastic Surgery
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• 제44권6호
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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.