• 대한방사선기술학회지:방사선기술과학
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• 제40권3호
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• pp.385-392
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• 2017

본 연구는 전산화단층촬영에서 관전압과 관전류에 따른 화질과 피폭선량을 연구하고 None IR과 IR (Iterative Reconstruction)의 단계에 따른 영상의 SNR(Signal to Noise Ratio)을 비교하여 영상 화질의 개선정도에 대하여 확인해보고자 하였다. Image J를 이용하여 화질을 측정한 결과 관전압의 증가에 따라 HU (Hounsfield units)와 BN(Background Noise)은 감소하였으며, 이와 반대로 SI (Signal Intensity)와 SNR, $CTDI_{vol}$ (CT dose in dex volume)은 관전압이 높아질수록 증가하였으며, BHU(Background Hounsfield Units)의 변화는 없었다. 관전류의 증가로 인해서 BN이 감소하였고, 반대로 SNR과 CTDI은 증가하였다. 또한 IR의 단계가 높아질수록 HU와 SI, BN이 낮아지고, SNR이 약 10~60% 향상됨을 알 수 있었다. 이를 토대로 임상에서 IR 적용 시 단계적 접근 방식으로 관전압과 관전류를 미세 조정하여 점차적으로 방사선량을 줄여 나가야 할 것이다.

• Maxillofacial Plastic and Reconstructive Surgery
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• 제38권
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• pp.46.1-46.7
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• 2016

Background: Osteoradionecrosis is the most dreadful complication after head and neck irradiation. Orocutaneous fistula makes patients difficult to eat food. Fibular free flap is the choice of the flap for mandibular reconstruction. Osteocutaneous flap can reconstruct both hard and soft tissues simultaneously. This study was to investigate the success rate and results of the free fibular flap for osteoradionecrosis of the mandible and which side of the flap should be harvested for better reconstruction. Methods: A total of eight consecutive patients who underwent fibula reconstruction due to jaw necrosis from March 2008 to December 2015 were included in this study. Patients were classified according to stages, primary sites, radiation dose, survival, and quality of life. Results: Five male and three female patients underwent operation. The mean age of the patients was 60.1 years old. Two male patients died of recurred disease of oral squamous cell carcinoma. The mean dose of radiation was 70.5 Gy. All fibular free flaps were survived. Five patients could eat normal diet after operation; however, three patients could eat only soft diet due to loss of teeth. Five patients reported no change of speech after operation, two reported worse speech ability, and one patient reported improved speech after operation. The ipsilateral side of the fibular flap was used when intraoral soft tissue defect with proximal side of the vascular pedicle is required. The contralateral side of the fibular flap was used when extraoral skin defect with proximal side of the vascular pedicle is required. Conclusions: Osteonecrosis of the jaw is hard to treat because of poor healing process and lack of vascularity. Free fibular flap is the choice of the surgery for jaw bone reconstruction and soft tissue fistula repair. The design and selection of the right or left fibular is dependent on the available vascular pedicle and soft tissue defect sites.

• 대한방사선기술학회지:방사선기술과학
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• 제40권2호
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• pp.261-267
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• 2017

저 선량 흉부 전산화단층촬영(low dose computed tomography; LDCT)검사 시 기존의 검사방법인 필터보정역투영법인 FBP(filted back projection)와 적응식 통계적 반복 재구성법인 ASIR(adaptive statistical iterative reconstruction)의 적용 및 관전압 변화에 따른 영상의 화질과 피폭선량을 비교 평가해 보고자 하였다. 흉부 phantom을 이용하여 재구성방법에 따라 FBP와 ASIR적용(10%, 20%)을 하였고, 관전압(100kVp, 120kVp)에 변화를 주어 실험을 하였다. 화질평가를 위해 back-ground noise와 signal-noise ratio(SNR), contrast-noise ratio(CNR)를 구하였으며, 선량평가를 위해 CTDIvol과 DLP를 구하였다. 화질평가에 있어 kVp에 따른 ascending aorta(AA) SNR과 inpraspinatus muscle(IM) SNR은 AA SNR과 IM SNR은 유의한 차이가 있었다(p < 0.05). 선량평가에 있어 CTDIvol과 DLP는 유의한 차이가 있었으며(p < 0.05), CTDIvol은 120 kVp, FBP가 2.6 mGy, 120 kVp, 10%-ASIR가 2.38 mGy, 120kVp, 20%-ASIR가 2.17 mGy로 0.43 mGy 감소하였고, 100 kVp, FBP가 1.61 mGy, 100 kVp, 10%-ASIR가 1.48 mGy, 100 kVp, 20%-ASIR가 1.34 mGy로 0.27 mGy 감소하였다. 또한 DLP에서는 120 kVp, FBP가 $103.21mGy{\cdot}cm$, 120 kVp, 10%-ASIR가 $94.57mGy{\cdot}cm$, 120 kVp, 20%-ASIR가 $85.94mGy{\cdot}cm$로 $17.27mGy{\cdot}cm$(16.7%) 감소하였고, 100 kVp, FBP가 $63.87mGy{\cdot}cm$, 100 kVp, 10%-ASIR가 $58.54mGy{\cdot}cm$, 100 kVp, 20%-ASIR가 $53.25mGy{\cdot}cm$로 $10.62mGy{\cdot}cm$(16.7%)로 감소하였다. 재구성방법에 따른 FBP와 ASIR 10%, 20%에서는 화질의 변화 없이 선량을 줄일 수 있어 흉부 low dose CT검사 시 ASIR 20%적용하여 검사하는 것이 좋으며, 관전압 변화에 따른 120 kVp와 100 kVp에서는 선량은 크게 줄어들었지만, noise가 증가하여 화질이 떨어지는 것으로 나타났다.

• Korean Journal of Radiology
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• 제22권6호
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• pp.983-993
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• 2021

Objective: To investigate the image quality of ultralow-dose CT (ULDCT) of the chest reconstructed using a cycle-consistent generative adversarial network (CycleGAN)-based deep learning method in the evaluation of pulmonary tuberculosis. Materials and Methods: Between June 2019 and November 2019, 103 patients (mean age, 40.8 ± 13.6 years; 61 men and 42 women) with pulmonary tuberculosis were prospectively enrolled to undergo standard-dose CT (120 kVp with automated exposure control), followed immediately by ULDCT (80 kVp and 10 mAs). The images of the two successive scans were used to train the CycleGAN framework for image-to-image translation. The denoising efficacy of the CycleGAN algorithm was compared with that of hybrid and model-based iterative reconstruction. Repeated-measures analysis of variance and Wilcoxon signed-rank test were performed to compare the objective measurements and the subjective image quality scores, respectively. Results: With the optimized CycleGAN denoising model, using the ULDCT images as input, the peak signal-to-noise ratio and structural similarity index improved by 2.0 dB and 0.21, respectively. The CycleGAN-generated denoised ULDCT images typically provided satisfactory image quality for optimal visibility of anatomic structures and pathological findings, with a lower level of image noise (mean ± standard deviation [SD], 19.5 ± 3.0 Hounsfield unit [HU]) than that of the hybrid (66.3 ± 10.5 HU, p < 0.001) and a similar noise level to model-based iterative reconstruction (19.6 ± 2.6 HU, p > 0.908). The CycleGAN-generated images showed the highest contrast-to-noise ratios for the pulmonary lesions, followed by the model-based and hybrid iterative reconstruction. The mean effective radiation dose of ULDCT was 0.12 mSv with a mean 93.9% reduction compared to standard-dose CT. Conclusion: The optimized CycleGAN technique may allow the synthesis of diagnostically acceptable images from ULDCT of the chest for the evaluation of pulmonary tuberculosis.

• 한국방사선학회논문지
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• 제11권7호
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• pp.679-685
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• 2017

환자의 병변 진단에 효과적인 CT 검사가 광범위하게 실시되고 있어, 방사선 피폭이 매우 크게 증가하였다. 환자의 피폭 선량을 줄이기 위해 다양한 방법이 강구되고 있고, 영상재구성 측면에서 반복 재구성 기법이 적용되고 있다. 반복 재구성 기법 중 대수적 재구성 기법의 정규화 인자에 대한 재구성된 단면 영상의 품질을 정규화 제곱평균제곱근 오차를 이용하여 조사하였다. 프로그램은 Visual C++로 작성하였으며 평행빔하에서 $512{\times}512$ 크기의 Shepp-Logan 두부 팬텀, 360장의 투영 영상, 1024개의 검출기 픽셀을 적용하였고, 전방투영과 역투영에 Joseph 방법을 사용하였다. 0.09-0.12의 정규화 인자에서 10회 반복으로 최소의 NRMS값 0.108을 얻었고 0.1% 및 0.2%의 잡음에 대해 8회 및 6회에서 최적의 영상을 보였다. 사용하는 팬텀에 따라 최적화된 값의 변동이 관찰되어 ART를 사용할 경우 정규화 인자에 대해서는 case-by-case로 최적의 값을 찾아야 한다는 것을 알 수 있다. 대수적 재구성 기법에서 최적의 정규화 인자를 발견함으로써 단면 영상을 획득하는데 걸리는 시간을 단축할 수 있을 것이다.

• 대한의용생체공학회:의공학회지
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• 제36권4호
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• pp.123-127
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• 2015

Recently, new gamma camera systems enabling low radiation dose imaging have been developed. We reviewed the recent development of these low dose gamma camera systems including high sensitivity detectors, device structures, noise reduction filters, efficient image reconstruction algorithms, low dose protocols, and so on. It is expected that further technological advances reduce both radiation dose and imaging time in gamma camera imaging especially for radiation-sensitive patients such as pediatric patients.

• 한국방사선학회논문지
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• 제17권1호
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• pp.1-9
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• 2023

전산화단층촬영조영술(computer tomography angiography, CTA)의 최적 화질을 위한 서로 다른 요오드 농도와 스캔 매개변수를 적용하여 필터 보정 역투영 (filtered back projection, FBP), 혼합형 반복재구성 (hybrid-iterative reconstruction, hybrid-IR) 및 딥러닝 재구성 (deep learning reconstruction, DLR)의 화질적 특성을 정량적으로 평가하였다. 320행 검출기 CT 스캐너에서 지름 19 cm의 원통형 물 팬텀 가장자리에 있는 다양한 요오드 농도 (1.2, 2.9, 4.9, 6.9, 10.4, 14.3, 18.4 및 25.9 mg/mL)의 팬텀을 스캔하였다. 각각의 재구성 기술을 사용하여 획득한 데이터는 노이즈 (noise), 변동 계수 (coefficient of variation, COV) 및 평균 제곱근 오차 (root mean square error, RMSE)을 통해 영상을 분석하였다. 요오드의 농도가 증가할수록 CT number 값은 증가하였지만 노이즈 변화는 특별한 특성을 보이지 않았다. 다양한 관전류 및 관전압에서 FBP, adaptive iterative dose reduction (AIDR) 3D 및 advanced intelligent clear-IQ engine (AiCE)에 대해 요오드 농도를 증가할수록 COV는 감소하였고 요오드 농도가 낮을 때는 재구성 기술 간의 COV 차이가 다소 발생하였지만, 요오드 농도가 높아짐에 따라 그 차이는 미약한 결과를 보였다. 또한, AiCE에서는 요오드 농도가 높아질수록 RMSE는 감소하지만 특정한 농도 (4.9 mg/mL) 이후에는 RMSE가 오히려 증가 되는 특성을 보여주었다. 따라서 최적의 CTA 영상 획득을 위해 재구성 기술에 따른 요오드 농도의 변화 및 다양한 관전류 및 관전압의 스캔 매개변수의 특성을 고려하여 환자 스캔을 해야 할 것이다.

• 한국의학물리학회지:의학물리
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• 제29권4호
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• pp.150-156
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• 2018

This study aims to develop an improved Feldkamp-Davis-Kress (FDK) reconstruction algorithm using anisotropic total variation (ATV) minimization to enhance the image quality of low-dose cone-beam computed tomography (CBCT). The algorithm first applies a filter that integrates the Shepp-Logan filter into a cosine window function on all projections for impulse noise removal. A total variation objective function with anisotropic penalty is then minimized to enhance the difference between the real structure and noise using the steepest gradient descent optimization with adaptive step sizes. The preserving parameter to adjust the separation between the noise-free and noisy areas is determined by calculating the cumulative distribution function of the gradient magnitude of the filtered image obtained by the application of the filtering operation on each projection. With these minimized ATV projections, voxel-driven backprojection is finally performed to generate the reconstructed images. The performance of the proposed algorithm was evaluated with the catphan503 phantom dataset acquired with the use of a low-dose protocol. Qualitative and quantitative analyses showed that the proposed ATV minimization provides enhanced CBCT reconstruction images compared with those generated by the conventional FDK algorithm, with a higher contrast-to-noise ratio (CNR), lower root-mean-square-error, and higher correlation. The proposed algorithm not only leads to a potential imaging dose reduction in repeated CBCT scans via lower mA levels, but also elicits high CNR values by removing noisy corrupted areas and by avoiding the heavy penalization of striking features.

• Korean Journal of Radiology
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• 제22권1호
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• pp.131-138
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• 2021

Objective: Iterative reconstruction degrades image quality. Thus, further advances in image reconstruction are necessary to overcome some limitations of this technique in low-dose computed tomography (LDCT) scan of the chest. Deep-learning image reconstruction (DLIR) is a new method used to reduce dose while maintaining image quality. The purposes of this study was to evaluate image quality and noise of LDCT scan images reconstructed with DLIR and compare with those of images reconstructed with the adaptive statistical iterative reconstruction-Veo at a level of 30% (ASiR-V 30%). Materials and Methods: This retrospective study included 58 patients who underwent LDCT scan for lung cancer screening. Datasets were reconstructed with ASiR-V 30% and DLIR at medium and high levels (DLIR-M and DLIR-H, respectively). The objective image signal and noise, which represented mean attenuation value and standard deviation in Hounsfield units for the lungs, mediastinum, liver, and background air, and subjective image contrast, image noise, and conspicuity of structures were evaluated. The differences between CT scan images subjected to ASiR-V 30%, DLIR-M, and DLIR-H were evaluated. Results: Based on the objective analysis, the image signals did not significantly differ among ASiR-V 30%, DLIR-M, and DLIR-H (p = 0.949, 0.737, 0.366, and 0.358 in the lungs, mediastinum, liver, and background air, respectively). However, the noise was significantly lower in DLIR-M and DLIR-H than in ASiR-V 30% (all p < 0.001). DLIR had higher signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) than ASiR-V 30% (p = 0.027, < 0.001, and < 0.001 in the SNR of the lungs, mediastinum, and liver, respectively; all p < 0.001 in the CNR). According to the subjective analysis, DLIR had higher image contrast and lower image noise than ASiR-V 30% (all p < 0.001). DLIR was superior to ASiR-V 30% in identifying the pulmonary arteries and veins, trachea and bronchi, lymph nodes, and pleura and pericardium (all p < 0.001). Conclusion: DLIR significantly reduced the image noise in chest LDCT scan images compared with ASiR-V 30% while maintaining superior image quality.

• 대한의용생체공학회:의공학회지
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• 제35권5호
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• pp.132-141
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• 2014

In an ordinary CT scan, a large number of projections with full field-of-view (FFOV) are necessary to reconstruct high resolution images. However, excessive x-ray dosage is a great concern in FFOV scan. Region-of-interest (ROI) CT or sparse-view CT is considered to be a solution to reduce x-ray dosage in CT scanning, but it suffers from bright-band artifacts or streak artifacts giving contrast anomaly in the reconstructed image. In this study, we propose an image reconstruction method to eliminate the bright-band artifacts and the streak artifacts simultaneously. In addition to the ROI scan for the interior projection data with relatively high sampling rate in the view direction, we get sparse-view exterior projection data with much lower sampling rate. Then, we reconstruct images by solving a constrained total variation (TV) minimization problem for the interior projection data, which is assisted by the exterior projection data in the compressed sensing (CS) framework. For the interior image reconstruction assisted by the exterior projection data, we implemented the proposed method which enforces dual data fidelity terms and a TV term. The proposed method has effectively suppressed the bright-band artifacts around the ROI boundary and the streak artifacts in the ROI image. We expect the proposed method can be used for low-dose CT scans based on limited x-ray exposure to a small ROI in the human body.