77 research outputs found

    Non-blind deconvolution with an alternating direction method of multipliers (ADMM) after noise reduction in nondestructive testing

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    Abstract: To ensure the quality of material, nondestructive testing is necessary, and radiography testing is the nondestructive technique most commonly used today. For inspection, the quality of a radiographic image is critical, and there are many image artifacts that can reduce inspection accuracies such as noise or blurring. The deterioration in spatial resolution caused by blur in both the X-ray imaging itself and the noise reduction process are particular problems. To tackle them, we implemented a non-blind deconvolution method that employs the alternating direction method of multipliers (ADMM) after noise reduction. Experimental results confirm that the proposed algorithm effectively restores edge sharpness. The 50% modulation transfer function of the restored image of a slit-camera was about 3.54 line-pairs per mm, which is about 2.5 times higher than that of the denoised image. Moreover, the edge preservation index values are about 0.82, 0.54, and 0.75 for the restored, denoised, and acquired images, respectively. Consequentially, the proposed method has the potential to increase inspection efficiency in industrial applications.ope

    Single-scan patient-specific scatter correction in computed tomography using peripheral detection of scatter and compressed sensing scatter retrieval

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    PURPOSE: X-ray scatter results in a significant degradation of image quality in computed tomography (CT), representing a major limitation in cone-beam CT (CBCT) and large field-of-view diagnostic scanners. In this work, a novel scatter estimation and correction technique is proposed that utilizes peripheral detection of scatter during the patient scan to simultaneously acquire image and patient-specific scatter information in a single scan, and in conjunction with a proposed compressed sensing scatter recovery technique to reconstruct and correct for the patient-specific scatter in the projection space. METHODS: The method consists of the detection of patient scatter at the edges of the field of view (FOV) followed by measurement based compressed sensing recovery of the scatter through-out the projection space. In the prototype implementation, the kV x-ray source of the Varian TrueBeam OBI system was blocked at the edges of the projection FOV, and the image detector in the corresponding blocked region was used for scatter detection. The design enables image data acquisition of the projection data on the unblocked central region of and scatter data at the blocked boundary regions. For the initial scatter estimation on the central FOV, a prior consisting of a hybrid scatter model that combines the scatter interpolation method and scatter convolution model is estimated using the acquired scatter distribution on boundary region. With the hybrid scatter estimation model, compressed sensing optimization is performed to generate the scatter map by penalizing the L1 norm of the discrete cosine transform of scatter signal. The estimated scatter is subtracted from the projection data by soft-tuning, and the scatter-corrected CBCT volume is obtained by the conventional Feldkamp-Davis-Kress algorithm. Experimental studies using image quality and anthropomorphic phantoms on a Varian TrueBeam system were carried out to evaluate the performance of the proposed scheme. RESULTS: The scatter shading artifacts were markedly suppressed in the reconstructed images using the proposed method. On the Catphanยฉ504 phantom, the proposed method reduced the error of CT number to 13 Hounsfield units, 10% of that without scatter correction, and increased the image contrast by a factor of 2 in high-contrast regions. On the anthropomorphic phantom, the spatial nonuniformity decreased from 10.8% to 6.8% after correction. CONCLUSIONS: A novel scatter correction method, enabling unobstructed acquisition of the high frequency image data and concurrent detection of the patient-specific low frequency scatter data at the edges of the FOV, is proposed and validated in this work. Relative to blocker based techniques, rather than obstructing the central portion of the FOV which degrades and limits the image reconstruction, compressed sensing is used to solve for the scatter from detection of scatter at the periphery of the FOV, enabling for the highest quality reconstruction in the central region and robust patient-specific scatter correction.ope

    Deep Learning-Based Decision-Tree Classifier for COVID-19 Diagnosis From Chest X-ray Imaging

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    The global pandemic of coronavirus disease 2019 (COVID-19) has resulted in an increased demand for testing, diagnosis, and treatment. Reverse transcription polymerase chain reaction (RT-PCR) is the definitive test for the diagnosis of COVID-19; however, chest X-ray radiography (CXR) is a fast, effective, and affordable test that identifies the possible COVID-19-related pneumonia. This study investigates the feasibility of using a deep learning-based decision-tree classifier for detecting COVID-19 from CXR images. The proposed classifier comprises three binary decision trees, each trained by a deep learning model with convolution neural network based on the PyTorch frame. The first decision tree classifies the CXR images as normal or abnormal. The second tree identifies the abnormal images that contain signs of tuberculosis, whereas the third does the same for COVID-19. The accuracies of the first and second decision trees are 98 and 80%, respectively, whereas the average accuracy of the third decision tree is 95%. The proposed deep learning-based decision-tree classifier may be used in pre-screening patients to conduct triage and fast-track decision making before RT-PCR results are available.ope

    Evaluation of Fabricated Semiconductor Sensor for Verification of ฮณ-ray Distribution in Brachytherapy

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    In radiation therapy fields, a brachytherapy is a treatment that kills lesion of cells by inserting a radioisotope that keeps emitting radiation into the body. We currently verify the consistency of radiation treatment plan and dose distribution through film/screen system (F/S system), provide therapy after checking dose. When we check dose distribution, F/S systems have radiation signal distortion because there is low resolution by penumbra depending on the condition of film developed. In this study, We fabricated a HgI2 Semiconductor radiation sensor for base study in order that we verify the real dose distribution weather it's same as plans or not in brachytherapy. Also, we attempt to evaluate the feasibility of QA system by utilizing and evaluating the sensor to bracytherapy source. As shown in the result of detected signal with various source-to-detector distance (SDD), we quantitatively verified the real range of treatment which is also equivalent to treatment plans because only the low signal estimated as scatters was measured beyond the range of treatment. And the result of experiment that we access reproducibility on the same condition of ฮณ-ray, we have made sure that the CV (coefficient of variation) is within 1.5 percent so we consider that the HgI2 sensor is available at QA of brachytherapy based on the result.ope

    Hybrid model-based and deep learning-based metal artifact reduction method in dental cone-beam computed tomography

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    Objective: To present a hybrid approach that incorporates a constrained beam-hardening estimator (CBHE) and deep learning (DL)-based post-refinement for metal artifact reduction in dental cone-beam computed tomography (CBCT). Methods: Constrained beam-hardening estimator (CBHE) is derived from a polychromatic X-ray attenuation model with respect to X-ray transmission length, which calculates associated parameters numerically. Deep-learning-based post-refinement with an artifact disentanglement network (ADN) is performed to mitigate the remaining dark shading regions around a metal. Artifact disentanglement network (ADN) supports an unsupervised learning approach, in which no paired CBCT images are required. The network consists of an encoder that separates artifacts and content and a decoder for the content. Additionally, ADN with data normalization replaces metal regions with values from bone or soft tissue regions. Finally, the metal regions obtained from the CBHE are blended into reconstructed images. The proposed approach is systematically assessed using a dental phantom with two types of metal objects for qualitative and quantitative comparisons. Results: The proposed hybrid scheme provides improved image quality in areas surrounding the metal while preserving native structures. Conclusion: This study may significantly improve the detection of areas of interest in many dentomaxillofacial applications. ยฉ 2023 Korean Nuclear Societyope

    Anisotropic Total Variation Denoising Technique for Low-Dose Cone-Beam Computed Tomography Imaging

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    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 conebeam 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.ope

    Low-dose CBCT reconstruction via joint non-local total variation denoising and cubic B-spline interpolation

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    This study develops an improved Feldkamp-Davis-Kress (FDK) reconstruction algorithm using non-local total variation (NLTV) denoising and a cubic B-spline interpolation-based backprojector to enhance the image quality of low-dose cone-beam computed tomography (CBCT). The NLTV objective function is minimized on all log-transformed projections using steepest gradient descent optimization with an adaptive control of the step size to augment the difference between a real structure and noise. The proposed algorithm was evaluated using a phantom data set acquired from a low-dose protocol with lower milliampere-seconds (mAs).The combination of NLTV minimization and cubic B-spline interpolation rendered the enhanced reconstruction images with significantly reduced noise compared to conventional FDK and local total variation with anisotropic penalty. The artifacts were remarkably suppressed in the reconstructed images. Quantitative analysis of reconstruction images using low-dose projections acquired from low mAs showed a contrast-to-noise ratio with spatial resolution comparable to images reconstructed using projections acquired from high mAs. The proposed approach produced the lowest RMSE and the highest correlation. These results indicate that the proposed algorithm enables application of the conventional FDK algorithm for low mAs image reconstruction in low-dose CBCT imaging, thereby eliminating the need for more computationally demanding algorithms. The substantial reductions in radiation exposure associated with the low mAs projection acquisition may facilitate wider practical applications of daily online CBCT imaging.ope

    A Study on Acceptance of Voice-based Virtual Secretary in Smart Home

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ๊ธฐ์ˆ ๊ฒฝ์˜ยท๊ฒฝ์ œยท์ •์ฑ…์ „๊ณต, 2018. 8. ํ™ฉ์ค€์„.2010๋…„ ์ดํ›„๋ถ€ํ„ฐ ์—ฐ๊ฒฐ ๊ฐ€๋Šฅํ•œ IoT๊ธฐ๊ธฐ๋“ค์ด ์ธ๊ตฌ ์ˆ˜๋ฅผ ๋„˜์–ด์„œ๋ฉฐ ๊ทธ ์ˆ˜๋Š” ๊ธฐํ•˜๊ธ‰์ˆ˜์ ์œผ๋กœ ์ฆ๊ฐ€ํ•˜๋Š” ์ƒํ™ฉ์—์„œ IoT๊ธฐ๊ธฐ๋“ค์˜ ํ†ตํ•ฉ ๋ฐ ํ”Œ๋žซํผํ™”๊ฐ€ ์ง„ํ–‰๋˜๊ณ  ์žˆ๋‹ค. ๊ฐœ์ธ ๊ฐ€์ • ์ธก๋ฉด์—์„œ๋„ Smart Home Appliance๋“ค์˜ ํ†ตํ•ฉ์ด ์š”๊ตฌ๋˜๋Š” ๊ฐ€์šด๋ฐ ์Šค๋งˆํŠธํ™ˆ ์‚ฐ์—…์ด ๋น ๋ฅด๊ฒŒ ์„ฑ์žฅํ•˜๊ณ  ์žˆ์œผ๋ฉฐ ์Šค๋งˆํŠธํ™ˆ์˜ ํ—ˆ๋ธŒ๋กœ์„œ ์Œ์„ฑ๊ฐ€์ƒ๋น„์„œ๊ฐ€ ๋…๋ณด์ ์ธ ๊ธฐ์ˆ ๋กœ ์ž๋ฆฌ๋งค๊น€ํ•˜๊ณ  ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์Šค๋งˆํŠธํ™ˆ์˜ ์Œ์„ฑ๊ฐ€์ƒ๋น„์„œ์˜ ์บ์ฆ˜๋ฐœ์ƒ์— ๋Œ€ํ•œ ๊ฐ€๋Šฅ์„ฑ์—์„œ ์ถœ๋ฐœํ•˜์—ฌ ๊ธฐ์ˆ ์ˆ˜์šฉ๋ชจ๋ธ(TAM)์„ ์ด์šฉํ•˜์—ฌ ์Šค๋งˆํŠธํ™ˆ์˜ ์Œ์„ฑ๊ฐ€์ƒ๋น„์„œ ์ˆ˜์šฉ์˜ ๊ฒฐ์ •์š”์ธ์„ ์‹๋ณ„ํ•˜๊ณ  ์บ์ฆ˜ ์ „, ํ›„์˜ ํ˜์‹ ์ง‘๋‹จ์˜ ์ฐจ์ด๋ฅผ ๋ณด๊ธฐ ์œ„ํ•ด ํ˜์‹ ๊ณ ์ง‘๋‹จ๊ณผ ํ˜์‹ ์ €์ง‘๋‹จ์œผ๋กœ ๋‚˜๋ˆ„์–ด ๋‹ค์ค‘์ง‘๋‹จ๋ถ„์„์„ ํ†ตํ•ด ์˜ํ–ฅ๋„์ฐจ์ด๋ฅผ ๋ณด๋Š” ๊ฒƒ์„ ๋…ผ๋ฌธ์˜ ๋ชฉ์ ๊ณผ ์—ฐ๊ตฌ๋ฐฉ๋ฒ•์œผ๋กœ ์„ค์ •ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๋Š” ๊ธฐ์ˆ ์ˆ˜์šฉ๋ชจ๋ธ(TAM)์— Perceived Risk๋ฅผ ํฌํ•จํ•œ ํ™•์žฅ๋œ ํ˜•ํƒœ์˜ ๋ชจ๋ธ์„ ์ฐจ์šฉํ•˜์—ฌ ๋…๋ฆฝ๋ณ€์ˆ˜๋กœ์„œ ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜๊ณผ ๋น„์„œ์ ์š”์†Œ์ธ ๊ฐ์ •์  ๋Œ€ํ™” ์œ ๋„์„ฑ, ๋น„์„œ์  ๊ธฐ๋Šฅ์„ฑ, ํ†ตํ•ฉ์  ๋ฏธ๋””์–ด ์ œ๊ณต ๊ธฐ๋Šฅ์„ฑ๊ณผ ์Šค๋งˆํŠธํ™ˆ ์ œ์–ด์™€ ๊ธฐ๋Šฅ์  ์š”์†Œ์ธ ์Šค๋งˆํŠธํ™ˆ ๊ฐ€์ „์˜ ์ œ์–ด์˜ ์ •๋„ ๋ฐ ํ˜ธํ™˜์„ฑ, ๊ฒฝ๋น„/๊ฐ์‹œ ๊ธฐ๋Šฅ์„ฑ๊ณผ ๋ฆฌ์Šคํฌ์  ์š”์†Œ์ธ ์‚ฌ์ƒํ™œ ์นจํ•ด ์œ„ํ—˜, ์žฌ๋ฌด์  ์œ„ํ—˜, ๊ธฐ๋Šฅ์  ์œ„ํ—˜์„ ์„ค์ •ํ•˜์˜€๋‹ค. ๋˜ํ•œ ํ˜์‹ ์„ฑ์„ DSI๊ธฐ์ค€์œผ๋กœ ์ธก์ •ํ•˜์—ฌ ์ „์ฒด์ง‘๋‹จ์„ ํ˜์‹ ์„ฑ์˜ ํ‰๊ท ์œผ๋กœ ๋‚˜๋ˆ  ํ˜์‹ ๊ณ ์ง‘๋‹จ๊ณผ ํ˜์‹ ์ €์ง‘๋‹จ์œผ๋กœ ๊ตฌ๋ถ„ํ•˜์˜€๋‹ค. ์ „์ฒด ์ง‘๋‹จ ๋ถ„์„๊ฒฐ๊ณผ ๋น„์„œ์  ๊ธฐ๋Šฅ์„ฑ, ์Šค๋งˆํŠธํ™ˆ ๊ธฐ๊ธฐ ์ œ์–ด์˜ ์ •๋„ ๋ฐ ํ˜ธํ™˜์„ฑ์ด ์œ ์šฉ์„ฑ๊ณผ ์šฉ์ด์„ฑ์— ๋ชจ๋‘ ์˜ํ–ฅ์„ ๋ฏธ์ณ ์ค‘์š”ํ•œ ์š”์ธ์œผ๋กœ ํŒŒ์•…์ด ๋˜์—ˆ๊ณ , ํ†ตํ•ฉ์  ๋ฏธ๋””์–ด ์ œ๊ณต์˜ ๊ธฐ๋Šฅ์„ฑ, ๊ฒฝ๋น„/๊ฐ์‹œ ๊ธฐ๋Šฅ์„ฑ, ๊ธฐ๋Šฅ์  ์œ„ํ˜‘์ด ์‚ฌ์šฉ์œ ์šฉ์„ฑ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์š”์ธ์œผ๋กœ ๋ถ„์„๋˜์—ˆ๋‹ค. ๋˜ํ•œ ์œ ์šฉ์„ฑ๊ณผ ์šฉ์ด์„ฑ ์ค‘ ์‚ฌ์šฉ์˜๋„์— ์œ ์šฉ์„ฑ๋งŒ ์œ ์˜๋ฏธํ•œ ์˜ํ–ฅ์„ ๋ฏธ์ณ ์ˆ˜์šฉ์ž๋“ค์ด ํŽธ๋ฆฌ์„ฑ๋ณด๋‹ค ๋ชฉ์ ์„ฑ์„ ๋” ์ค‘์‹œํ•œ๋‹ค๋Š” ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๊ณ , ์žฌ๋ฌด์  ์œ„ํ—˜์ด ์ˆ˜์šฉ์˜๋„์— ์ง์ ‘์ ์ธ ์•…์˜ํ–ฅ์„ ์ฃผ๋Š” ๊ฒƒ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ํ˜์‹ ๊ณ ์ง‘๋‹จ๊ณผ ํ˜์‹ ์ €์ง‘๋‹จ์˜ ์˜ํ–ฅ๋„ ์ฐจ์ด ๋ถ„์„์˜ ๊ฒฐ๊ณผ๋กœ, ์Šค๋งˆํŠธํ™ˆ ๊ธฐ๊ธฐ ์ œ์–ด์˜ ์ •๋„ ๋ฐ ํ˜ธํ™˜์„ฑ์ด ํ˜์‹ ์ €์ง‘๋‹จ์—์„œ๋งŒ ์ค‘์š”ํ•œ ์š”์†Œ๋กœ ์ž‘์šฉํ•จ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๊ณ , ๊ฒฝ๋น„/๊ฐ์‹œ ๊ธฐ๋Šฅ์„ฑ, ํ†ตํ•ฉ์  ๋ฏธ๋””์–ด ์ œ๊ณต์˜ ๊ธฐ๋Šฅ์„ฑ์ด ํ˜์‹ ๊ณ ์ง‘๋‹จ์—์„œ ๊ธ์ •์  ์š”์†Œ๋กœ ์ž‘์šฉํ•จ์„ ์•Œ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ „์ฒด์ง‘๋‹จ ๋ถ„์„๊ณผ ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ ํ˜์‹์ €์ง‘๋‹จ์—์„œ๋Š” ์žฌ๋ฌด์  ์œ„ํ—˜์ด ์‚ฌ์šฉ์˜๋„์— ๋ถ€์ •์  ์˜ํ–ฅ์„ ์ฃผ์—ˆ์ง€๋งŒ ํ˜์‹ ๊ณ ์ง‘๋‹จ์—์„œ๋Š” ์˜คํžˆ๋ ค ์‚ฌ์šฉ์œ ์šฉ์„ฑ์— ๊ธ์ •์ ์ธ ์˜ํ–ฅ์„ ์ฃผ์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์Šค๋งˆํŠธํ™ˆ ์Œ์„ฑ๊ฐ€์ƒ๋น„์„œ์˜ ์ˆ˜์šฉ์— ๋ฏธ์น˜๋Š” ์š”์ธ๋“ค์„ ๋ถ„์„ํ•œ ํšจ์‹œ์  ์—ฐ๊ตฌ์ด๋ฉฐ ์ œํ’ˆ์ž์ฒด๊ฐ€ ๊ณ ์œ ํ•˜๊ฒŒ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ์†์„ฑ์— ์ดˆ์ ์„ ๋งž์ถฐ ์Šค๋งˆํŠธํ™ˆ ์Œ์„ฑ๊ฐ€์ƒ๋น„์„œ์˜ ์ˆ˜์šฉ์š”์ธ ๋ถ„์„์— ํŠนํ™”๋œ ๋…ผ๋ฌธ์ด๋ผ๋Š” ํ•™์ˆ ์  ์˜์˜๊ฐ€ ์žˆ์œผ๋ฉฐ, ๊ธฐ๋ณธ์ ์ธ ์ œํ’ˆ ์ˆ˜์šฉ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์š”์ธ๋“ค์„ ๋ถ„์„ํ•˜๋Š” ๊ฒƒ์„ ๋ฌผ๋ก , ํ˜์‹ ๊ณ ์ง‘๋‹จ๊ณผ ํ˜์‹ ์ €์ง‘๋‹จ์˜ ๋‹ค์ค‘์ง‘๋‹จ ๋ถ„์„์œผ๋กœ ์บ์ฆ˜์˜ ๊ฒฝ๊ณ„์˜ ์ „๊ธฐ ์ง‘๋‹จ๊ณผ ํ›„๊ธฐ์ง‘๋‹จ์˜ ์ฐจ์ด๋ฅผ ๋ถ„์„ํ•˜์—ฌ ๊ตฌ์ฒด์ ์ธ ์ „๋žต์— ๋Œ€ํ•ด ํ†ต์ฐฐ์„ ์ œ๊ณตํ•œ๋‹ค๋Š” ์ ์—์„œ ์‚ฐ์—…์ ์ธ ์˜์˜ ๋˜ํ•œ ์žˆ๋‹ค.์ดˆ ๋ก iii ๋ชฉ ์ฐจ v ํ‘œ ๋ชฉ์ฐจ viii ๊ทธ๋ฆผ ๋ชฉ์ฐจ ix 1. ์„œ๋ก  1 1.1 ์—ฐ๊ตฌ๋ฐฐ๊ฒฝ 1 1.2 ์—ฐ๊ตฌ๋ชฉ์  6 2. ์ด๋ก ์  ๋ฐฐ๊ฒฝ 7 2.1 ์Šค๋งˆํŠธํ™ˆ์˜ ์Œ์„ฑ๊ฐ€์ƒ ๋น„์„œ 7 2.1.1 ๊ฐ€์ƒ๋น„์„œ์˜ ์ •์˜ 7 2.1.2 ์Šค๋งˆํŠธํ™ˆ๊ณผ ์Œ์„ฑ๊ฐ€์ƒ๋น„์„œ์˜ ๊ด€๊ณ„ ๋ฐ ์Šค๋งˆํŠธํ™ˆ์˜ ์Œ์„ฑ๊ฐ€์ƒ ๋น„์„œ์˜ ์ •์˜ 8 2.2 ์Šค๋งˆํŠธํ™ˆ์˜ ์Œ์„ฑ๊ฐ€์ƒ๋น„์„œ์™€ ์บ์ฆ˜ 9 2.2.1 ์Šค๋งˆํŠธํ™ˆ ์Œ์„ฑ๊ฐ€์ƒ๋น„์„œ์™€ ์บ์ฆ˜์˜ ๊ด€๊ณ„ 13 2.2.2 ์บ์ฆ˜๊ณผ ๊ฐœ์ธ์˜ ํ˜์‹ ์„ฑ๊ณผ์˜ ๊ด€๊ณ„ ๋ฐ ์—ฐ๊ตฌ 14 2.3 ์‹ ๊ธฐ์ˆ  ์ˆ˜์šฉ์˜ ์š”์ธ์„ ์ฐพ๊ธฐ ์œ„ํ•œ ์—ฐ๊ตฌ๋ชจํ˜• 17 2.3.1 ๊ธฐ์ˆ ์ˆ˜์šฉ๋ชจ๋ธ(TAM, Technology Acceptance Model) 17 2.3.2 Featherman ๊ธฐ์ˆ ์ˆ˜์šฉ๋ชจ๋ธ์˜ ๊ฐœ๋… ๋ฐ ์œ ์šฉ์„ฑ 20 2.4 ์™ธ๋ถ€๋ณ€์ˆ˜์— ๋Œ€ํ•œ ๊ณ ์ฐฐ 21 2.4.1 ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜๊ณผ ๋น„์„œ์  ์š”์†Œ 21 2.4.2 ์Šค๋งˆํŠธํ™ˆ ์ œ์–ด์™€ ๊ธฐ๋Šฅ์  ์š”์†Œ 23 2.4.3 ๋ฆฌ์Šคํฌ์  ์š”์†Œ 25 2.4.4 ๋ณ€์ˆ˜์˜ ์กฐ์ž‘์  ์ •์˜ 26 3. ์—ฐ๊ตฌ์„ค๊ณ„ 30 3.1 ์—ฐ๊ตฌ๋ชจํ˜• 30 3.2 ์—ฐ๊ตฌ๊ฐ€์„ค ์„ค์ • 31 3.2.1 ์ปค๋ฎค๋‹ˆ์ผ€์ด์…˜๊ณผ ๋น„์„œ์  ์š”์†Œ์˜ ๊ฐ€์„ค 31 3.2.2 ์Šค๋งˆํŠธํ™ˆ ์ œ์–ด์™€ ๊ธฐ๋Šฅ์  ์š”์†Œ์˜ ๊ฐ€์„ค 33 3.2.3 ๋ฆฌ์Šคํฌ ์š”์†Œ์˜ ๊ฐ€์„ค 34 3.2.4 ์ง€๊ฐ๋œ ์‚ฌ์šฉ์œ ์šฉ์„ฑ, ์‚ฌ์šฉ์šฉ์ด์„ฑ๊ณผ ์‚ฌ์šฉ์˜๋„์˜ ๊ฐ€์„ค 35 4. ๋ถ„์„๊ฒฐ๊ณผ 36 4.1 ์ธ๊ตฌํ†ต๊ณ„ํ•™์  ํŠน์„ฑ 36 4.2 ํƒ€๋‹น์„ฑ ๋ฐ ์‹ ๋ขฐ๋„ ๊ฒ€์ฆ 38 4.2.1 ๋ณ€์ˆ˜๋“ค์˜ ํƒ์ƒ‰์  ์š”์ธ๋ถ„์„ 39 4.2.2 ๋ณ€์ˆ˜๋“ค์˜ ํ™•์ธ์  ์š”์ธ๋ถ„์„ 46 4.3 ํŒ๋ณ„ํƒ€๋‹น์„ฑ 51 4.4 ์—ฐ๊ตฌ๋ชจํ˜•์˜ ๋ถ„์„๊ฒฐ๊ณผ 53 4.5 ๊ฐ„์ ‘ํšจ๊ณผ ๊ฒ€์ฆ 60 4.6 ํ˜์‹ ์ง‘๋‹จ์— ๋”ฐ๋ฅธ ๋‹ค์ค‘์ง‘๋‹จ๋ถ„์„ 61 5. ๊ฒฐ๋ก  65 5.1 ์—ฐ๊ตฌ ์š”์•ฝ 65 5.2 ์—ฐ๊ตฌ ์‹œ์‚ฌ์  67 5.3 ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ ๋ฐ ํ–ฅํ›„ ์—ฐ๊ตฌ 70 ์ฐธ ๊ณ  ๋ฌธ ํ—Œ(๊ตญ๋‚ด) 72 ์ฐธ ๊ณ  ๋ฌธ ํ—Œ(ํ•ด์™ธ) 78 ๋ถ€๋ก 1 : ์„ค๋ฌธ์กฐ์‚ฌ 85 Abstract 99Maste

    Compact bunker shielding assessment for 1.5 T MR-Linac

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    This study evaluated the effect of the 1.5 T magnetic field of the magnetic resonance-guided linear accelerator (MR-Linac) on the radiation leakage doses penetrating the bunker radiation shielding wall. The evaluated 1.5 T MR-Linac Unity system has a bunker of the minimum recommended size. Unlike a conventional Linac, both primary beam transmission and secondary beam leakage were considered independently in the design and defined at the machine boundary away from the isocenter. Moreover, additional shielding was designed considering the numerous ducts between the treatment room and other rooms. The Linac shielding was evaluated by measuring the leakage doses at several locations. The intrinsic vibration and magnetic field were inspected at the proposed isocenter of the system. For verification, leakage doses were measured before and after applying the magnetic field. The intrinsic vibration and magnetic field readings were below the permitted limit. The leakage dose (0.05-12.2 ยตSv/week) also complied with internationally stipulated limits. The special shielding achieved a five-fold reduction in leakage dose. Applying the magnetic field increased the leakage dose by 0.12 to 4.56 ยตSv/week in several measurement points, although these values fall within experimental uncertainty. Thus, the effect of the magnetic field on the leakage dose could not be ascertained.ope

    Feasibility of hybrid TomoHelical- and TomoDirect-based volumetric gradient matching technique for total body irradiation

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    Background: Tomotherapy-based total body irradiation (TBI) is performed using the head-first position (HFP) and feet-first position (FFP) due to treatment length exceeding the 135 cm limit. To reduce the dosimetric variation at the match lines, we propose and verify a volumetric gradient matching technique (VGMT) by combining TomoHelical (TH) and TomoDirect (TD) modes. Methods: Two planning CT image sets were acquired with HFP and FFP using 15 ร— 55 ร— 18 cm3 of solid water phantom. Planning target volume (PTV) was divided into upper, lower, and gradient volumes. The junction comprised 2-cm thick five and seven gradient volumes (5-GVs and 7-GVs) to create a dose distribution with a gentle slope. TH-IMRT and TD-IMRT plans were generated with 5-GVs and 7-GVs. The setup error in the calculated dose was assessed by shifting dose distribution of the FFP plan by 5, 10, 15, and 20 mm in the longitudinal direction and comparing it with the original. Doses for 95% (D95) and 5% of the PTV (D5) were calculated for all simulated setup error plans. Absolute dose measurements were performed using an ionization chamber in the junction. Results: The TH&TD plan produced a linear gradient in junction volume, comparable to that of the TH&TH plan. D5 of the PTV was 110% of the prescribed dose when the FFP plan was shifted 0.7 cm and 1.2 cm in the superior direction for 5-GVs and 7-GVs. D95 of the PTV decreased to < 90% of the prescribed dose when the FF plan was shifted 1.1 cm and 1.3 cm in the inferior direction for 5-GVs and 7-GVs. The absolute measured dose showed a good correlation with the calculated dose in the gradient junction volume. The average percent difference (ยฑSD) in all measured points was โˆ’ 0.7 ยฑ 1.6%, and the average dose variations between depths was โˆ’ 0.18 ยฑ 1.07%. Conclusion: VGMT can create a linear dose gradient across the junction area in both TH&TH and TH&TD and can minimize the dose sensitivity to longitudinal setup errors in tomotherapy-based TBI.ope
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