• Journal of the Korean Wood Science and Technology
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• 제33권5호통권133호
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• pp.21-28
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• 2005

For the proper conservation of wooden cultural properties, non-destructive evaluation (NDE) method, which can be used to quantitatively evaluate the internal state of wood members, are needed. In this study, an ultrasonic CT system composed of portable devices was attempted, and the capacity of this system was verified by reconstructing the CT images for two phantoms and two artificially defected specimens. Results from this study showed that the sizes of detected defects were enlarged and the shapes were distorted on the CT images. Also, the positions were shifted somewhat toward the surface of specimen, which is regarded due to the anisotropic property of wood. Compared to the filtered back-projection method, SIRT (simultaneous iterative reconstruction technique) method was determined to be more efficient as the algorithm of image reconstruction for wood. A new ultrasonic CT system is thought to be used as a NDE method for wood. However wood characteristics and wave diffraction within wood made it difficult to accurately evaluate the size, shape and position of defects. To improve the quality of CT image of wood, more research including the relationship between wood and ultrasound is needed, and wood properties should be taken into consideration on the image reconstruction algorithm.

• International Journal of Aeronautical and Space Sciences
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• 제14권4호
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• pp.398-407
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• 2013

Optical tomography was used to measure the pattern of spray cross-section. The maximum-likelihood estimation (MLE) algorithm was used to reconstruct the spray cross-section from the measured transmission rate of the spray. A swirl-type injector was used to form an optically dense spray, and the test was carried out in a high-pressure chamber, to control the pressure condition of the test site. Before the experiment, the reliability of the MLE-based reconstruction algorithm was verified, by comparing it with a conventional filtered back projection reconstruction (FBP) method. The MLE algorithm showed superior reconstruction of the image. In the spray patternation experiment, the results of the optical tomography and optical line patternator, which uses Mie scattering signal information, were compared. While measuring the cross-section of optically dense spray, the intensity of the scattering signal had attenuated to an uncorrectable level, which led to incorrect spray pattern measurement by the optical line patternator. However, reliable results were obtained by optical tomography, under the same condition. Finally, the pattern of the optically dense spray was measured at various chamber pressures, of up to 3 MPa. As the chamber pressure increased, the hollow cone-shaped swirl spray shrank, and the attenuation coefficient value of the inner region increased.

• Nuclear Engineering and Technology
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• 제53권3호
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• pp.888-893
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• 2021

The International Atomic Energy Agency has developed a tomographic imaging system for accomplishing the total fuel rod-by-rod verification time of fuel assemblies within the order of 1-2 h, however, there are still limitations for some fuel types. The aim of this study is to develop a deep learning-based denoising process resulting in increasing the tomographic image acquisition speed of fuel assembly compared to the conventional techniques. Convolutional AutoEncoder (CAE) was employed for denoising the low-quality images reconstructed by filtered back-projection (FBP) algorithm. The image data set was constructed by the Monte Carlo method with the FBP and ground truth (GT) images for 511 patterns of missing fuel rods. The de-noising performance of the CAE model was evaluated by comparing the pixel-by-pixel subtracted images between the GT and FBP images and the GT and CAE images; the average differences of the pixel values for the sample image 1, 2, and 3 were 7.7%, 28.0% and 44.7% for the FBP images, and 0.5%, 1.4% and 1.9% for the predicted image, respectively. Even for the FBP images not discriminable the source patterns, the CAE model could successfully estimate the patterns similarly with the GT image.

• Nuclear Engineering and Technology
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• 제55권5호
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• pp.1527-1532
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• 2023

The noise reduction algorithm using the non-local means (NLM) approach is very efficient in nuclear medicine imaging. In this study, the applicability of the NLM noise reduction algorithm in single-photon emission computed tomography (SPECT) images with a brain phantom and the optimization of the NLM algorithm by changing the smoothing factors according to various reconstruction methods are investigated. Brain phantom images were reconstructed using filtered back projection (FBP) and ordered subset expectation maximization (OSEM). The smoothing factor of the NLM noise reduction algorithm determined the optimal coefficient of variation (COV) and contrast-to-noise ratio (CNR) results at a value of 0.020 in the FBP and OSEM reconstruction methods. We confirmed that the FBP- and OSEM-based SPECT images using the algorithm applied with the optimal smoothing factor improved the COV and CNR by 66.94% and 8.00% on average, respectively, compared to those of the original image. In conclusion, an optimized smoothing factor was derived from the NLM approach-based algorithm in brain SPECT images and may be applicable to various nuclear medicine imaging techniques in the future.

• Current Optics and Photonics
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• 제8권3호
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• pp.246-258
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• 2024

In aerospace and energy engineering, the reconstruction of three-dimensional (3D) temperature distributions is crucial. Traditional methods like algebraic iterative reconstruction and filtered back-projection depend on voxel division for resolution. Our algorithm, blending deep learning with computer graphics rendering, converts 2D projections into light rays for uniform sampling, using a fully connected neural network to depict the 3D temperature field. Although effective in capturing internal details, it demands multiple cameras for varied angle projections, increasing cost and computational needs. We assess the impact of camera number on reconstruction accuracy and efficiency, conducting butane-flame simulations with different camera setups (6 to 18 cameras). The results show improved accuracy with more cameras, with 12 cameras achieving optimal computational efficiency (1.263) and low error rates. Verification experiments with 9, 12, and 15 cameras, using thermocouples, confirm that the 12-camera setup as the best, balancing efficiency and accuracy. This offers a feasible, cost-effective solution for real-world applications like engine testing and environmental monitoring, improving accuracy and resource management in temperature measurement.

• Nuclear Engineering and Technology
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• 제55권12호
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• pp.4591-4596
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• 2023

Single-photon emission computed tomography SPECT image reconstruction methods have a significant influence on image quality, with filtered back projection (FBP) and ordered subset expectation maximization (OSEM) being the most commonly used methods. In this study, we proposed newly-designed adaptive non-blind deconvolution with a structural similarity (SSIM) index that can take advantage of the FBP and OSEM image reconstruction methods. After acquiring brain SPECT images, the proposed image was obtained using an algorithm that applied the SSIM metric, defined by predicting the distribution and amount of blurring. As a result of the contrast to noise ratio (CNR) and coefficient of variation evaluation (COV), the resulting image of the proposed algorithm showed a similar trend in spatial resolution to that of FBP, while obtaining values similar to those of OSEM. In addition, we confirmed that the CNR and COV values of the proposed algorithm improved by approximately 1.69 and 1.59 times, respectively, compared with those of the algorithm involving an inappropriate deblurring process. To summarize, we proposed a new type of algorithm that combines the advantages of SPECT image reconstruction techniques and is expected to be applicable in various fields.

• 방사성폐기물학회지
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• 제18권2호
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• pp.217-225
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• 2020

해체 원전에서 총 폐기물의 약 70~80%에 해당하는 많은 양의 콘크리트 폐기물은 해체 폐기물의 대부분을 차지한다. 해체 시 발생된 콘크리트 폐기물은 핵종별 농도에 따라 규제해제 폐기물과 방사성폐기물로 정의할 수 있다. 따라서, 방사성 콘크리트 폐기물의 처분 비용을 저감하기 위하여 자체 처분 및 제한적 재활용을 위한 제염 작업의 수행이 중요하다. 그러므로 콘크리트 폐기물의 효율적인 제염 작업을 위해 내부 방사능 분포를 예측하는 것이 필수적이다. 본 연구는 원전 해체 시, 발생되는 콘크리트 폐기물의 내부 방사능 분포를 예측하기 위하여 다양한 컴프턴 영상 재구성 방법의 성능을 비교하였다. 다양한 컴프턴 영상 재구성 방법으로 단순 역투사(SBP), 필터 후 역투사(FBP), 최대우도 기댓값 최대화 방법(MLEM), 그리고 기존의 MLEM의 시스템 반응 함수에 에너지 정보가 결합되어 확률적으로 계산하는 최대우도 기댓값 최대화 방법(E-MLEM)이 사용되었다. 재구성된 영상을 획득한 후, 정량적인 분석 방법을 이용하여 재구성된 영상의 성능을 정량적으로 비교 및 평가하였다. MLEM 및 E-MLEM 영상 재구성 방법은 각각 재구성된 영상에서 높은 이미지 분해능과 신호 대 잡음비를 유지하는 데 있어 가장 좋은 성능을 보여주었다. 본 연구에서 도출된 결과들은 원자력 시설 해체 시 방사성 콘크리트 폐기물의 내부 방사능 분포를 예측하기 위한 수단으로 컴프턴 영상을 사용할 수 있는 가능성을 보여주었다.

• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 2002년도 Proceedings
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• pp.432-435
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• 2002

We have developed and proposed the heavy ion CT system which consists of fluorescent screen and CCD camera equipped with image intensifier. In our system, we have measured the residual range of particles that passed a phantom and reconstructed the CT image for the distribution of relative stopping power by filtered back projection method with Shepp '||'&'||' Logan filter. The heavy ion $\^$12/C accelerated up to 400 MeV/u by HIMAC (Heavy Ion Medical Accelerator in Chiba) was used. Intensity of the beam output changes like macro pulse, the period being 3.3 sec and the width being 2 sec. The series of data was acquired in synchronizing with the pulse, leading to the improvement of S/N in the CT image. The fundamental performance was experimentally evaluated in the proposed system. The spatial resolution was estimated to be about 1 mm and the density resolution (electron density referred to water) to be about 0.01.

• 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.

• 한국의학물리학회지:의학물리
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• 제32권4호
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• pp.92-98
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• 2021

Purpose: This study automatically discriminates homogeneous and structure edge regions on computed tomography (CT) images, and it evaluates the noise level and edge preservation ratio (EPR) according to the different types of iterative reconstruction (IR). Methods: The dataset consisted of CT scans of 10 patients reconstructed with filtered back projection (FBP), statistical IR (iDose⁴), and iterative model-based reconstruction (IMR). Using the 10th and 85th percentiles of the structure coherence feature, homogeneous and structure edge regions were localized. The noise level was estimated using the averages of the standard deviations for five regions of interests (ROIs), and the EPR was calculated as the ratio of standard deviations between homogeneous and structural edge regions on subtraction CT between the FBP and IR. Results: The noise levels were 20.86±1.77 Hounsfield unit (HU), 13.50±1.14 HU, and 7.70±0.46 HU for FBP, iDose⁴, and IMR, respectively, which indicates that iDose⁴ and IMR could achieve noise reductions of approximately 35.17% and 62.97%, respectively. The EPR had values of 1.14±0.48 and 1.22±0.51 for iDose⁴ and IMR, respectively. Conclusions: The iDose⁴ and IMR algorithms can effectively reduce noise levels while maintaining the anatomical structure. This study suggested automated evaluation measurements of noise levels and EPRs, which are important aspects in CT image quality with patients' cases of FBP, iDose⁴, and IMR. We expect that the inclusion of other important image quality indices with a greater number of patients' cases will enable the establishment of integrated platforms for monitoring both CT image quality and radiation dose.