• Title/Summary/Keyword: iterative back-projection

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CT Image Reconstruction of Wood Using Ultrasound Velocities II - Determination of the Initial Model Function of the SIRT Method -

  • 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.29-37
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    • 2005
  • A previous study verified that the SIRT (simultaneous iterative reconstruction technique) method is more efficient than the back-projection method as a CT algorithm for wood. However, it was expected that the determination of the initial model function of the SIRT method would influence the quality of CT image. Therefore, in this study, we intended to develop a technique that could be used to determine an adequate initial model function. For this purpose, we proposed several techniques, and for each technique we examined the effects of the initial model function on the average errors and the CT image at each iteration. Through this study, it was shown that the average error was decreased and the image quality was improved using the proposed techniques. This tendency was most pronounced when the back-projection method was used to determine the initial model function. From the results of this study, we drew the following conclusions: 1) The initial model function of the SIRT method should be determined with careful attention, and 2) the back-projection method efficiently determines the initial model function of the SIRT method.

Super-resolution image enhancement by Papoulis-Gerchbergmethod improvement (Papoulis-Gerchberg 방법의 개선에 의한 초해상도 영상 화질 향상)

  • Jang, Hyo-Sik;Kim, Duk-Gyoo;Jung, Yoon-Soo;Lee, Tae-Gyoun;Won, Chul-Ho
    • Journal of Sensor Science and Technology
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    • v.19 no.2
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    • pp.118-123
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    • 2010
  • This paper proposes super-resolution reconstruction algorithm for image enhancement. Super-resolution reconstruction algorithms reconstruct a high-resolution image from multi-frame low-resolution images of a scene. Conventional super- resolution reconstruction algorithms are iterative back-projection(IBP), robust super-resolution(RS)method and standard Papoulis-Gerchberg(PG)method. However, traditional methods have some problems such as rotation and ringing. So, this paper proposes modified algorithm to improve the problem. Experimental results show that this proposed algorithm solve the problem. As a result, the proposed method showed an increase in the PSNR for traditional super-resolution reconstruction algorithms.

Fast Calculation Algorithm for Line Integral on CT Reconstruction (CT 영상재구성을 위한 빠른 선적분 알고리즘)

  • Kwon Su, Chon;Joon-Min, Gil
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.1
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    • pp.41-46
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    • 2023
  • Iterative reconstruction of CT takes a long time because projection and back-projection are alternatively repeated until taking a good image. To reduce the reconstruction time, we need a fast algorithm for calculating the projection which is a time-consuming step. In this paper, we proposed a new algorithm to calculate the line integral and the algorithm is approximately 10% faster than the well-known Siddon method (Jacobs version) and has a good image quality. Although the algorithm has been investigated for the case of parallel beams, it can be extended to the case of fan and cone beam geometries in the future.

RECONSTRUCTING A SUPER-RESOLUTION IMAGE FOR DEPTH-VARYING SCENES

  • Yokoyamay, Ami;Kubotaz, Akira;Hatoriz, Yoshinori
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.446-449
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    • 2009
  • In this paper, we present a novel method for reconstructing a super-resolution image using multi-view low-resolution images captured for depth varying scene without requiring complex analysis such as depth estimation and feature matching. The proposed method is based on the iterative back projection technique that is extended to the 3D volume domain (i.e., space + depth), unlike the conventional superresolution methods that handle only 2D translation among captured images.

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Effects of ADMIRE Algorithms on Fat Measurements Using Computed Tomography (CT) (CT를 이용한 지방측정에 ADMIRE 알고리즘이 미치는 영향)

  • Lee, Chang Wook;Lee, Sang Heon;Im, In Chul;Lee, Hyo Yeong
    • Journal of the Korean Society of Radiology
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    • v.13 no.3
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    • pp.465-472
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    • 2019
  • To investigate the effects of iterative reconstruction algorithms on fat measurements using computed tomography (CT), we comparatively and quantitatively analyzed the ratios of visceral, subcutaneous, and visceral-subcutaneous fat areas as well as the variations of HU and noise of visceral and subcutaneous fat using ADMIRE strength and attempted to identify any difference between them. Experimental results showed that no statistically significant difference existed among the visceral, subcutaneous, and visceral-subcutaneous fat area ratios HU of visceral fat area and HU of subcutaneous fat area when applying ADMIRE as compared with existing conventional filtered back projection algorithms. However, as the ADMIRE strength increases, the noise of visceral and subcutaneous fat decreases by up to 12.1% and 19.2%, respectively. In conclusion, iterative reconstruction algorithms have no effect on the visceral, subcutaneous, and visceral-subcutaneous fat area ratios, which are indicators of fat measurement using CT.

Application of sigmoidal optimization to reconstruct nuclear medicine image: Comparison with filtered back projection and iterative reconstruction method

  • Shin, Han-Back;Kim, Moo-Sub;Law, Martin;Djeng, Shih-Kien;Choi, Min-Geon;Choi, Byung Wook;Kang, Sungmin;Kim, Dong-Wook;Suh, Tae Suk;Yoon, Do-Kun
    • Nuclear Engineering and Technology
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    • v.53 no.1
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    • pp.258-265
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    • 2021
  • High levels for noise and a loss of true signal make the quantitative interpretation of nuclear medicine (NM) images difficult. An application of profile optimization using a sigmoidal function in this study was used to acquire the NM images with high quality. And the images were acquired by using three kinds of reconstruction method using each same sinogram: a standard filtered back-projection (FBP), an iterative reconstruction (IR) technique, and the sigmoidal function profile optimization (SFPO). Comparison of image according to reconstruction method was performed to show a superiority of the SFPO for imaging. The images reconstructed by using the SFPO showed an average of 1.49 times and of 1.17 times better in contrast than the results obtained using the standard FBP and the IR technique, respectively. Higher signal to noise ratios were obtained as an average of 12.30 times and of 3.77 times than results obtained using the standard FBP and the IR technique, respectively. This study confirms that reconstruction with SFPO (vs FBP and vs IR) can lead to better lesion detectability and characterization with noise reduction. It can be developed for future reconstruction technique for the NM imaging.

A Study on the Usefulness of Deep Learning Image Reconstruction with Radiation Dose Variation in MDCT (MDCT에서 선량 변화에 따른 딥러닝 재구성 기법의 유용성 연구)

  • Ga-Hyun, Kim;Ji-Soo, Kim;Chan-Deul, Kim;Joon-Pyo, Lee;Joo-Wan, Hong;Dong-Kyoon, Han
    • Journal of the Korean Society of Radiology
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    • v.17 no.1
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    • pp.37-46
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    • 2023
  • This study aims to evaluate the usefulness of Deep Learning Image Reconstruction (TrueFidelity, TF), the image quality of existing Filtered Back Projection (FBP) and Adaptive Statistical Iterative Reconstruction-Veo (ASIR-V) were compared. Noise, CNR, and SSIM were measured by obtaining images with doses fixed at 17.29 mGy and altered to 10.37 mGy, 12.10 mGy, 13.83 mGy, and 15.56 mGy in reconstruction techniques of FBP, ASIR-V 50%, and TF-H. TF-H has superior image quality compared to FBP and ASIR-V when the reconstruction technique change is given at 17.29 mGy. When dose changes were made, Noise, CNR, and SSIM were significantly different when comparing 10.37 mGy TF-H and FBP (p<0.05), and no significant difference when comparing 10.37 mGy TF-H and ASIR-V 50% (p>0.05). TF-H has a dose-reduction effect of 30%, as the highest dose of 15.56 mGy ASIR-V has the same image quality as the lowest dose of 10.37 mGy TF-H. Thus, Deep Learning Reconstruction techniques (TF) were able to reduce dose compared to Iterative Reconstruction techniques (ASIR-V) and Filtered Back Projection (FBP). Therefore, it is considered to reduce the exposure dose of patients.

Characterization of Deep Learning-Based and Hybrid Iterative Reconstruction for Image Quality Optimization at Computer Tomography Angiography (전산화단층촬영조영술에서 화질 최적화를 위한 딥러닝 기반 및 하이브리드 반복 재구성의 특성분석)

  • Pil-Hyun, Jeon;Chang-Lae, Lee
    • Journal of the Korean Society of Radiology
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    • v.17 no.1
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    • pp.1-9
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    • 2023
  • For optimal image quality of computer tomography angiography (CTA), different iodine concentrations and scan parameters were applied to quantitatively evaluate the image quality characteristics of filtered back projection (FBP), hybrid-iterative reconstruction (hybrid-IR), and deep learning reconstruction (DLR). A 320-row-detector CT scanner scanned a phantom with various iodine concentrations (1.2, 2.9, 4.9, 6.9, 10.4, 14.3, 18.4, and 25.9 mg/mL) located at the edge of a cylindrical water phantom with a diameter of 19 cm. Data obtained using each reconstruction technique was analyzed through noise, coefficient of variation (COV), and root mean square error (RMSE). As the iodine concentration increased, the CT number value increased, but the noise change did not show any special characteristics. COV decreased with increasing iodine concentration for FBP, adaptive iterative dose reduction (AIDR) 3D, and advanced intelligent clear-IQ engine (AiCE) at various tube voltages and tube currents. In addition, when the iodine concentration was low, there was a slight difference in COV between the reconstitution techniques, but there was little difference as the iodine concentration increased. AiCE showed the characteristic that RMSE decreased as the iodine concentration increased but rather increased after a specific concentration (4.9 mg/mL). Therefore, the user will have to consider the characteristics of scan parameters such as tube current and tube voltage as well as iodine concentration according to the reconstruction technique for optimal CTA image acquisition.

Development of Unmatched System Model for Iterative Image Reconstruction for Pinhole Collimator of Imaging Systems in Nuclear Medicine (핀홀콜리메이터를 사용한 핵의학영상기기의 순환적 영상 재구성을 위한 비동일 시스템 모델 개발)

  • Bae, Jae-Keon;Bae, Seung-Bin;Lee, Ki-Sung;Kim, Yong-Kwon;Joung, Jin-Hun
    • Journal of radiological science and technology
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    • v.35 no.4
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    • pp.353-360
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    • 2012
  • Diverse designs of collimator have been applied to Single Photon Emission Computed Tomography (SPECT) according to the purpose of acquisition; thus, it is necessary to reflect geometric characteristic of each collimator for successive image reconstruction. This study carry out reconstruction algorithm for imaging system in nuclear medicine with pinhole collimator. Especially, we study to solve sampling problem which caused in the system model of pinhole collimator. System model for a maximum likelihood expectation maximization (MLEM) was developed based on the geometry of the collimator. The projector and back-projector were separately implemented based on the ray-driven and voxel-driven methods, respectively, to overcome sparse sampling problem. We perform phantom study for pinhole collimator by using geant4 application for tomographic emission(GATE) simulation tool. The reconstructed images show promising results. Designed iterative reconstruction algorithm with unmatched system model effective to remove sampling problem artefact. Proposed algorithm can be used not only for pinhole collimator but also for various collimator system of imaging system in nuclear medicine.

Effects of Advanced Modeled Iterative Reconstruction on Coronary Artery Calcium (CAC) Scores (ADMIRE가 관상동맥 칼슘(CAC) 점수에 미치는 영향)

  • Lee, Sang-Heon;Lee, Hyo-Young
    • Journal of the Korean Society of Radiology
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    • v.15 no.5
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    • pp.603-612
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    • 2021
  • The effect of Advanced Modeled Iterative Reconstruction (ADMIRE) on the coronary artery calcium (CAC) score of computed tomography was evaluated. Coronary artery calcium images (348 calcium, 6 groups, total of 2088 calcium) were acquired by 128-slice dual-source CT of 89 patients.Volume score and Agatston score were measured from images reconstructed with filtered back projection (FBP) and ADMIRE (1-5). The difference between FBP and ADMIRE Strength (1-5) was confirmed through the Kruskal-Wallis test, and the post-hoc analysis was performed using the Mann-Whitney U test based on FBP. Both volume score and Agatston score showed statistically significant differences between FBP and ADMIRE (1-5) (P=0.015, P=0.0.38). As a result of post hoc analysis, the volume score decreased to 9.5% in ADMIRE 4 (Z=-2.359, P=0.018) and 13.2% in ADMIRE 5 (Z=-3.113, P=0.002) based on FBP. Agatston score decreased to 10.4% in ADMIRE 4 (Z=-2.051, P=0.040) and 14.0% in ADMIRE 5 (Z=-2.718, P=0.007) based on FBP. High ADMIRE strength affected the volume score and Agatston score due to the decrease in calcium area. In addition, the change in the Density factor due to the decrease in Maximum HU may affect the calculation of the Agatston score.