• Title/Summary/Keyword: Back-Projection

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Improvement in Reconstruction Time Using Multi-Core Processor on Computed Tomography (다중코어 프로세서를 이용한 전산화단층촬영의 재구성 시간 개선)

  • Chon, Kwon Su
    • Journal of the Korean Society of Radiology
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    • v.9 no.7
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    • pp.487-493
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    • 2015
  • The reconstruction on the computed tomography requires much time for calculation. The calculation time rapidly increases with enlarging matrix size for improving image quality. Multi-core processor, multi-core CPU, has widely used nowadays and has provided the reduction of the calculation time through multi-threads. In this study, the calculation time of the reconstruction process would improved using multi-threads based on the multi-core processor. The Pthread and the OpenMP used for multi-threads were used in convolution and back projection steps that required much time in the reconstruction. The Pthread and the OpenMP showed similar results in the speedup and the efficiency.

CT Image Reconstruction of Wood Using Ultrasound Velocities I - Effects of Reconstruction Algorithms and Wood Characteristics -

  • Kim, Kwang-Mo;Lee, Jun-Jae
    • Journal of the Korean Wood Science and Technology
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    • v.33 no.5 s.133
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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.

Non-Local Means-based Gradual Super-Resolution via Linear Mappings (비국소적 평균법 기반 점진적 선형 매핑 초해상화 기법)

  • Choi, Jae-Seok;Kim, Munchurl
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2015.07a
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    • pp.75-77
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    • 2015
  • 디스플레이 해상도가 지속적으로 고해상화가 되면서, 기존 저해상도 영상을 고해상도 디스플레이 크기에 맞춰 해상도를 키우는 기법인 초해상화(super-resolution, SR) 기법에 많은 관심이 쏟아지고 있으며 이에 대한 많은 초해상화 논문들이 게재되었다. 이 중 현재 최상 품질의 고해상도 영상을 복원하는 한 초해상화 기법은, 입력 받은 저해상도 영상을 자가 예제(self-examples)로 사용하여 선형 매핑(linear mapping)을 통해 점진적으로 여러 레벨(level)를 거쳐 조금씩 키우는 방법이다. 이때 각 레벨마다 기존 저해상도 영상 크기로 반복적으로 줄여 오차를 줄이는 역투영법(back-projection)을 사용하는데, 이 방법은 처리된 영상에 시각적 품질을 낮추는 링 아티팩트(ringing artifacts)를 생산하며, 이는 매 레벨마다 계속 누적이 되어 고해상도 결과 이미지 품질에 악영향을 미치는 단점이 있다. 이를 보완하기 위해, 본 논문에서는 저해상도 정지 영상을 고해상도 정지 영상으로 점진적으로 키울 때 일반적인 역투영법 대신 비국소적 평균법(non-local means, NLM) 기반 역투영법을 사용하는 초해상화 기법을 제안한다. 제안하는 기법은 매 레벨마다 생기는 링 아티팩트를 효과적으로 제거하여 높은 시각적 품질의 고해상도 영상을 복원할 수 있게 한다. 실험을 통해 제안된 초해상화 기법을 사용 시 기존 초해상화 기법보다 향상된 고품질 고해상도 영상 복원이 가능한 것을 확인하였다.

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A Study on the Welding Conditions of Weldability of Team Welding for Galvanized Steel Sheets of Automotive (자동차용 아연도금강판의 심 용접조건과 용접성에 관한 연구)

  • 임재규;정균호;국중하
    • Journal of Welding and Joining
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    • v.19 no.1
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    • pp.27-32
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    • 2001
  • This paper is studied about welding conditions and weldability of seam welding for galvanized steel sheet of automotive. The fuel tank of automobile is made by seam welding to be required of airtight or oiltight. This method have required a short time for welding, simplicity operation progress and little HAZ. Especially, it has more less residual stress and transformation than different welding progress. So, this study is for decreasing the leakage occurrence rate and to make standard operating condition table anyone can operate easily. Therefore, this study is analyzed the optimum conditions of seam welding for making the automobile with galvanized steel sheets by means of observing the microstructure and configuration back projection, RT, tensile-shear strengths test and SEM. Optimum conditions of seam welding obtained as follows, current 17.2-17.6kA speed 1.0m/min weld time 4:10:6 and current 16.5-17.4kA, speed 0.83m/min, weld time 4:10:4 at t1.0, and current, 18.5-18.9kA, speed 0.8m/min, weld time 4:10:4 and current 16.5-17.4kA, speed 0.68m/mi, weld time 4:10:2 at t1.6.

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Dense Spray Patternation using Optical Tomography

  • Cho, Seongho;Park, Gujeong;Yoon, Youngbin
    • International Journal of Aeronautical and Space Sciences
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    • v.14 no.4
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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.

The motion estimation algorithm implemented by the color / shape information of the object in the real-time image (실시간 영상에서 물체의 색/모양 정보를 이용한 움직임 검출 알고리즘 구현)

  • Kim, Nam-Woo;Hur, Chang-Wu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.11
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    • pp.2733-2737
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    • 2014
  • Motion detection according to the movement and the change area detection method according to the background difference and the motion history image for use in a motion estimation technique using a real-time image, the motion detection method according to the optical flow, the back-projection of the histogram of the object to track for motion tracking At the heart of MeanShift center point of the object and the object to track, while used, the size, and the like due to the motion tracking algorithm CamShift, Kalman filter to track with direction. In this paper, we implemented the motion detection algorithm based on color and shape information of the object and verify.

Development of de-noised image reconstruction technique using Convolutional AutoEncoder for fast monitoring of fuel assemblies

  • Choi, Se Hwan;Choi, Hyun Joon;Min, Chul Hee;Chung, Young Hyun;Ahn, Jae Joon
    • Nuclear Engineering and Technology
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    • v.53 no.3
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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.

Experimental study of noise level optimization in brain single-photon emission computed tomography images using non-local means approach with various reconstruction methods

  • Seong-Hyeon Kang;Seungwan Lee;Youngjin Lee
    • Nuclear Engineering and Technology
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    • v.55 no.5
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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.

Implementation of medical image labeling web application for machine learning (기계학습을 위한 의료영상 라벨링 웹 애플리케이션 구현)

  • Lee, Chung-sub;Lim, Dong-Wook;Kim, Ji-Eon;Noh, Si-Hyeong;Yu, Yeong-Ju;Kim, Tae-Hoon;Jeong, Chang-Won
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.11a
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    • pp.602-605
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    • 2021
  • 최근 인공지능 연구가 활발히 진행되고 있는 가운데 국내외에서 오픈 데이터셋을 제공하고 있어 기술개발이 가속화되고 있다. 데이터셋은 지도학습을 위한 학습데이터로 라벨링 데이터를 포함하고 있어 다양한 라벨링 기능이 적용된 도구 개발이 필요하다. 본 논문에서는 의료영상의 라벨링 데이터를 정교하고 빠르게 생성하기 위한 라벨링 웹 애플리케이션에 대해서 기술한다. 이를 구현하기 위해서 Back Projection, Grabcut 기법을 이용한 반자동 방식과 기계학습 모델을 통해서 예측한 자동 방식의 라벨링 기능을 구현하였다. 이와 관련하여 라벨링 기능별 수행 결과를 근감소증 진단을 위한 영상 라벨링 수행결과와 정량분석 결과를 보였다.

Strategies to improve the range verification of stochastic origin ensembles for low-count prompt gamma imaging

  • Hsuan-Ming Huang
    • Nuclear Engineering and Technology
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    • v.55 no.10
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    • pp.3700-3708
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    • 2023
  • The stochastic origin ensembles method with resolution recovery (SOE-RR) has been proposed to reconstruct proton-induced prompt gammas (PGs), and the reconstructed PG image was used for range verification. However, due to low detection efficiency, the number of valid events is low. Such a low-count condition can degrade the accuracy of the SOE-RR method for proton range verification. In this study, we proposed two strategies to improve the reconstruction of the SOE-RR algorithm for low-count PG imaging. We also studied the number of iterations and repetitions required to achieve reliable range verification. We simulated a proton beam (108 protons) irradiated on a water phantom and used a two-layer Compton camera to detect 4.44-MeV PGs. Our simulated results show that combining the SOE-RR algorithm with restricted volume (SOE-RR-RV) can reduce the error of the estimation of the Bragg peak position from 5.0 mm to 2.5 mm. We also found that the SOE-RR-RV algorithm initialized using a back-projection image could improve the convergence rate while maintaining accurate range verification. Finally, we observed that the improved SOE-RR algorithm set for 60,000 iterations and 25 repetitions could provide reliable PG images. Based on the proposed reconstruction strategies, the SOE-RR algorithm has the potential to achieve a positioning error of 2.5 mm for low-count PG imaging.