• Title/Summary/Keyword: Iterative reconstruction

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Projective Reconstruction from Multiple Images using Matrix Decomposition Constraints (행렬 분해 제약을 사용한 다중 영상에서의 투영 복원)

  • Ahn, Ho-Young;Park, Jong-Seung
    • Journal of Korea Multimedia Society
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    • v.15 no.6
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    • pp.770-783
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    • 2012
  • In this paper, we propose a novel structure recovery algorithm in the projective space using image feature points. We use normalized image feature coordinates for the numerical stability. To acquire an initial value of the structure and motion, we decompose the scaled measurement matrix using the singular value decomposition. When recovering structure and motion in projective space, we introduce matrix decomposition constraints. In the reconstruction procedure, a nonlinear iterative optimization technique is used. Experimental results showed that the proposed method provides proper accuracy and the error deviation is small.

A Comparison of Image Reconstruction Techniques for Electrical Resistance Tomography (Electrical Resistance Tomography의 영상복원 기법의 비교)

  • Kim, Ho-Chan;Boo, Chang-Jin;Lee, Yoon-Joon
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.19 no.3
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    • pp.119-126
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    • 2005
  • Electrical resistance tomography(ERT) maps resistivity values of the soil subsurface and characterizes buried objects. The characterization includes location, size and resistivity of buried objects. In this paper, Gauss-Newton, truncated least squares(TLS) and simultaneous iterative reconstruction technique(SIRT) methods are presented for the solution of the ERT image reconstruction. Computer simulations show that the spatial resolution of the reconstructed images by the TLS approach is improved as compared to those obtained by the Gauss-Newton and SIRT method.

Development of an Electrical Capacitance Tomography Code for Analysis of Two-Phase Flow in the Rectangular Pipe (사각관 이상유동 분석을 위한 전기적 캐패시턴스 토모그라피 코드 개발)

  • Lee, Kyoung-Hwang;Lee, Jae-Young
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.29 no.1 s.232
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    • pp.87-94
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    • 2005
  • A computer code for Electrical Capacitance Tomography (ECT) is developed to sense the cross sectional phase distribution of two-phase flow in the rectangular pipe in which the tomography sensor furnished by the insulated wall, electrodes, and electric field screen. The computer code had two steps for the image reconstruction. In the forward projection step, the sensitivity matrix was constructed based on the electric field calculated by the finite difference method. In the backward projection step, the sensitivity matrix and the measured capacitances were used to reconstruct the cross sectional image. Several algorithms including LBP, TR, ITR, and PLI were employed to find the proper one for the two-phase flow analysis. Since the dielectric constant of the water in two-phase flow is sensitive to the thermal parameter such as, temperature and pressure, the developed code was evaluated to find their accuracy, speed of calculation, and sensitivity to the variation of the dielectric constant. It was found that the iterative methods are superior to the direct methods for the image reconstruction, and the PLI method was the best in the variation of the dielectric constants.

Sampling Set Selection Algorithm for Weighted Graph Signals (가중치를 갖는 그래프신호를 위한 샘플링 집합 선택 알고리즘)

  • Kim, Yoon Hak
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.1
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    • pp.153-160
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    • 2022
  • A greedy algorithm is proposed to select a subset of nodes of a graph for bandlimited graph signals in which each signal value is generated with its weight. Since graph signals are weighted, we seek to minimize the weighted reconstruction error which is formulated by using the QR factorization and derive an analytic result to find iteratively the node minimizing the weighted reconstruction error, leading to a simplified iterative selection process. Experiments show that the proposed method achieves a significant performance gain for graph signals with weights on various graphs as compared with the previous novel selection techniques.

An Iterative Side Information Refinement Based on Block-Adaptive Search in Distributed Video Coding (분산 비디오 부호화에서 블록별 적응적 탐색에 기초한 반복적인 보조정보 보정기법)

  • Kim, Jin-Soo;Yun, Mong-Han;Kim, Jae-Gon;Seo, Kwang-Deok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.2
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    • pp.355-363
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    • 2011
  • Recently, as one of several methods to improve the performance of DVC(Distributed Video Coding) system, many research works are focusing on the iterative refinement of side information. Most of the conventional techniques are mainly based on the relationship between the reconstruction level and side information, or the vector median filtering of motion vectors, but, their performance improvements are restricted. In order to overcome the performance limit of the conventional schemes, in this paper, a side information generation scheme is designed by measuring the block-cost estimation. Then, by adaptively selecting the compensation mode using the received bit-plane information, we propose a block-adaptive iterative refinement which is efficient for non-symmetric moving objects. Computer simulations show that, by using the proposed refinement method, the performance can be improved up to 0.2 dB in rate-distortion.

Positron Emission Computed Tomographs and Image Reconstruction Methods (PET 장치와 화상 재구성법)

  • Lee, Man-Koo
    • Journal of radiological science and technology
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    • v.22 no.1
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    • pp.5-11
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    • 1999
  • This paper reviews recent major activities on instrumentation and methodology of PET. The performance of the PET instrumentation can be expressed by four physical characteristics, 1) spatial resolution, 2) coincidence resolving time, 3) energy resolution, and 4) detection efficiency. The physical and technical aspects of PET systems are briefly discussed along with these characteristics. Toward high resolution PET the recent trend has been to design multiple rings of densely packed detector arrays with scintillators. In order to satisfy the sampling requirement in reconstruction, continuous detector units has been developed. Iterative image reconstruction algorithms have received considerable attention for improvement of both the sampling requirement and image quality toward the stationary PET. Better resolving time improves the maximum true coincidence rate, which is also increased with more detectors placed in coincidence with each other. It suggests that volume PET is promising for enhancement of detection efficiency. The scattered coincidence event rate may be reduced by using detectors with better energy resolution. The use of interplane septa, however, takes over improvement of energy resolution in 2D PET. Energy resolution becomes an important factor for image quality under the condition of septa removal such as volume PET. Toward full utilization of emitting photons, 3D reconstruction incorporating oblique rays has been studied, and volume reconstruction algorithms have been developed. Practical volume PET systems impose heavy burden not only to detector sets and coincidence circuits, but also to computers in the memory requirements and the data processing. In conclusion, there have been many ingenious methods in development of PET instrumentation, which are based on unique capability of PET. They will be expected to overcome technical limitations, and to approach the fundamental limits.

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Regularized Adaptive High-resolution Image Reconstruction Considering Inaccurate Subpixel Registration (부정확한 부화소 단위의 위치 추정 오류에 적응적인 정규화된 고해상도 영상 재구성 연구)

  • Lee, Eun-Sil;Byun, Min;Kang, Moon-Gi
    • Journal of Broadcast Engineering
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    • v.8 no.1
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    • pp.19-29
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    • 2003
  • The demand for high-resolution images is gradually increasing, whereas many imaging systems yield aliased and undersampled images during image acquisition. In this paper, we propose a high-resolution image reconstruction algorithm considering inaccurate subpixel registration. A regularized Iterative reconstruction algorithm is adopted to overcome the ill-posedness problem resulting from inaccurate subpixel registration. In particular, we use multichannel image reconstruction algorithms suitable for application with multiframe environments. Since the registration error in each low-resolution has a different pattern, the regularization parameters are determined adaptively for each channel. We propose a methods for estimating the regularization parameter automatically. The preposed algorithm are robust against the registration error noise. and they do not require any prior information about the original image or the registration error process. Experimental results indicate that the proposed algorithms outperform conventional approaches in terms of both objective measurements and visual evaluation.

Image Quality and Lesion Detectability of Lower-Dose Abdominopelvic CT Obtained Using Deep Learning Image Reconstruction

  • June Park;Jaeseung Shin;In Kyung Min;Heejin Bae;Yeo-Eun Kim;Yong Eun Chung
    • Korean Journal of Radiology
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    • v.23 no.4
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    • pp.402-412
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    • 2022
  • Objective: To evaluate the image quality and lesion detectability of lower-dose CT (LDCT) of the abdomen and pelvis obtained using a deep learning image reconstruction (DLIR) algorithm compared with those of standard-dose CT (SDCT) images. Materials and Methods: This retrospective study included 123 patients (mean age ± standard deviation, 63 ± 11 years; male:female, 70:53) who underwent contrast-enhanced abdominopelvic LDCT between May and August 2020 and had prior SDCT obtained using the same CT scanner within a year. LDCT images were reconstructed with hybrid iterative reconstruction (h-IR) and DLIR at medium and high strengths (DLIR-M and DLIR-H), while SDCT images were reconstructed with h-IR. For quantitative image quality analysis, image noise, signal-to-noise ratio, and contrast-to-noise ratio were measured in the liver, muscle, and aorta. Among the three different LDCT reconstruction algorithms, the one showing the smallest difference in quantitative parameters from those of SDCT images was selected for qualitative image quality analysis and lesion detectability evaluation. For qualitative analysis, overall image quality, image noise, image sharpness, image texture, and lesion conspicuity were graded using a 5-point scale by two radiologists. Observer performance in focal liver lesion detection was evaluated by comparing the jackknife free-response receiver operating characteristic figures-of-merit (FOM). Results: LDCT (35.1% dose reduction compared with SDCT) images obtained using DLIR-M showed similar quantitative measures to those of SDCT with h-IR images. All qualitative parameters of LDCT with DLIR-M images but image texture were similar to or significantly better than those of SDCT with h-IR images. The lesion detectability on LDCT with DLIR-M images was not significantly different from that of SDCT with h-IR images (reader-averaged FOM, 0.887 vs. 0.874, respectively; p = 0.581). Conclusion: Overall image quality and detectability of focal liver lesions is preserved in contrast-enhanced abdominopelvic LDCT obtained with DLIR-M relative to those in SDCT with h-IR.

The Evaluation of Resolution Recovery Based Reconstruction Method, Astonish (Resolution Recovery 기반의 Astonish 영상 재구성 기법의 평가)

  • Seung, Jong-Min;Lee, Hyeong-Jin;Kim, Jin-Eui;Kim, Hyun-Joo;Kim, Joong-Hyun;Lee, Jae-Sung;Lee, Dong-Soo
    • The Korean Journal of Nuclear Medicine Technology
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    • v.15 no.1
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    • pp.58-64
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    • 2011
  • Objective: The 3-dimensional reconstruction method with resolution recovery modeling has advantages of high spatial resolution and contrast because of its precise modeling of spatial blurring according to the distance from detector plane. The aim of this study was to evaluate one of the resolution recovery reconstruction methods (Astonish, Philips Medical), compare it to other iterative reconstructions, and verify its clinical usefulness. Materials and Methods: NEMA IEC PET body phantom and Flanges Jaszczak ECT phantom (Data Spectrum Corp., USA) studies were performed using Skylight SPECT (Philips) system under four different conditions; short or long (2 times of short) radius, and half or full (40 kcts/frame) acquisition counts. Astonish reconstruction method was compared with two other iterative reconstructions; MLEM and 3D-OSEM which vendor supplied. For quantitative analysis, the contrast ratios obtained from IEC phantom test were compared. Reconstruction parameters were determined by optimization study using graph of contrast ratio versus background variability. The qualitative comparison was performed with Jaszczak ECT phantom and human myocardial data. Results: The overall contrast ratio was higher with Astonish than the others. For the largest hot sphere of 37 mm diameter, Astonish showed about 27.1% and 17.4% higher contrast ratio than MLEM and 3D-OSEM, in short radius study. For long radius, Astonish showed about 40.5% and 32.6% higher contrast ratio than MLEM and 3D-OSEM. The effect of acquired counts was insignificant. In the qualitative studies with Jaszczak phantom and human myocardial data, Astonish showed the best image quality. Conclusion: In this study, we have found out that Astonish can provide more reliable clinical results by better image quality compared to other iterative reconstruction methods. Although further clinical studies are required, Astonish would be used in clinics with confidence for enhancement of images.

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Image Reconstruction Using Iterative Regularization Scheme Based on Residual Error in Electrical Impedance Tomography (전기 임피던스 단층촬영법에서 잔류오차 기반의 반복적 조정기법을 이용한 영상 복원)

  • Kang, Suk-In;Kim, Kyung-Youn
    • Journal of IKEEE
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    • v.18 no.2
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    • pp.272-281
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    • 2014
  • In electrical impedance tomography (EIT), modified Newton Raphson (mNR) method is widely used inverse algorithm for static image reconstruction due to its convergence speed and estimation accuracy. The unknown conductivity distribution is estimated iteratively by minimizing a cost functional such that the residual error namely the difference in measured and calculated voltages is reduced. Although, mNR method has good estimation performance, EIT inverse problem still suffers from ill-conditioned and ill-posedness nature. To mitigate the ill-posedness, generally, regularization methods are adopted. The inverse solution is highly dependent on the choice of regularization parameter. In most cases, the regularization parameter has a constant value and is chosen based on experience or trail and error approach. In situations, when the internal distribution changes or with high measurement noise, the solution does not get converged with the use of constant regularization parameter. Therefore, in this paper, in order to improve the image reconstruction performance, we propose a new scheme to determine the regularization parameter. The regularization parameter is computed based on residual error and updated every iteration. The proposed scheme is tested with numerical simulations and laboratory phantom experiments. The results show an improved reconstruction performance when using the proposed regularization scheme as compared to constant regularization scheme.