• 제목/요약/키워드: Image reconstruction algorithm

검색결과 490건 처리시간 0.023초

Image Reconstruction using Simulated Annealing Algorithm in EIT

  • Kim Ho-Chan;Boo Chang-Jin;Lee Yoon-Joon
    • International Journal of Control, Automation, and Systems
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    • 제3권2호
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    • pp.211-216
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    • 2005
  • In electrical impedance tomography (EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically, the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents a simulated annealing technique as a statistical reconstruction algorithm for the solution of the static EIT inverse problem. Computer simulations with 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved as compared to that of the mNR algorithm at the expense of increased computational burden.

시뮬레이티드 어닐링을 이용한 전기임픽던스단층촬영법의 영상복원 (A Image Reconstruction Uing Simulated Annealing in Electrical Impedance Tomograghy)

  • 김호찬;부창진;이윤준
    • 대한전기학회논문지:시스템및제어부문D
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    • 제52권2호
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    • pp.120-127
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    • 2003
  • In electrical impedance tomography(EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents a simulated annealing technique as a statistical reconstruction algorithm for the solution of the static EIT inverse problem. Computer simulations with the 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved as compared to that of the mNR algorithm or genetic algorithm at the expense of increased computational burden.

염색체 영상의 재구성에 의한 형태학적 특징 파라메타 추출 (Morphological Feature Parameter Extraction from the Chromosome Image Using Reconstruction Algorithm)

  • 장용훈;이권순
    • 대한의용생체공학회:의공학회지
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    • 제17권4호
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    • pp.545-552
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    • 1996
  • Researches on chromosome are very significant in cytogenetics since a gene of the chromosome controls revelation of the inheritance plasma The human chromosome analysis is widely used to diagnose genetic disease and various congenital anomalies. Many researches on automated chromosome karyotype analysis has been carried out, some of which produced commercial systems. However, there still remains much room for improving the accuracy of chromosome classification. In this paper, we propose an algorithm for reconstruction of the chromosDme image to improve the chromosome classification accuracy. Morphological feature parameters are extracted from the reconstructed chromosome images. The reconstruction method from chromosome image is the 32 direction line algorithm. We extract three morphological feature parameters, centromeric index(C.I.), relative length ratio(R.L.), and relative area ratio(R.A.), by preprocessing ten human chromosDme images. The experimental results show that proposed algorithm is better than that of other researchers'comparing by feature parameter errors.

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개선된 FBP 토모그라픽 알고리즘에서 분해능의 결정 (The Determination of Resolution on the Improved FBP Tomographic Algorithm)

  • 구길모;황기환;박치승;고덕영
    • 대한전자공학회논문지TE
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    • 제42권1호
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    • pp.21-28
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    • 2005
  • 본 논문은 토모그라픽 영상시스템에 적합한 FBP 토모그라픽 영상복원 알고리즘의 분해능에 관하여 연구하였다. 고정좌표계를 이용하는 개선된 FBP 토모그라픽 영상복원 알고리즘으로부터 분해능을 분석할 수 있는 모호함수를 유도하였고, 이를 이용한 모의실험을 통하여 얻은 진폭분포로부터 측방향 및 축방향 분해능을 정량적으로 결정하였다. 개선된 FBP 토모그라픽 영상복원 알고리즘을 통해 기존의 SAM(Scanning Acoustic Microscope)시스템으로부터 얻을 수 있는 3dB와 6dB 축방향 분해능에 대해서도 각각 0.70 파장과 0.96 파장으로 SAM 영상의 3dB 축방향 분해능인 7 파장에 비하여 매우 개선된 분해능을 얻을 수 있음을 확인하였다. 평면 입사파의 회절 토모그라픽 영상복원을 위한 개선된 FBP 토모그라픽 영상복원 알고리즘은 미세하고 복잡한 다층 박막구조를 갖는 시료에 대하여 좋은 분해능을 갖는 토모그라픽 영상시스템을 개발하는데 유용하게 활용할 수 있도록 하였다.

Comparison of a Deep Learning-Based Reconstruction Algorithm with Filtered Back Projection and Iterative Reconstruction Algorithms for Pediatric Abdominopelvic CT

  • Wookon Son;MinWoo Kim;Jae-Yeon Hwang;Young-Woo Kim;Chankue Park;Ki Seok Choo;Tae Un Kim;Joo Yeon Jang
    • Korean Journal of Radiology
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    • 제23권7호
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    • pp.752-762
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    • 2022
  • Objective: To compare a deep learning-based reconstruction (DLR) algorithm for pediatric abdominopelvic computed tomography (CT) with filtered back projection (FBP) and iterative reconstruction (IR) algorithms. Materials and Methods: Post-contrast abdominopelvic CT scans obtained from 120 pediatric patients (mean age ± standard deviation, 8.7 ± 5.2 years; 60 males) between May 2020 and October 2020 were evaluated in this retrospective study. Images were reconstructed using FBP, a hybrid IR algorithm (ASiR-V) with blending factors of 50% and 100% (AV50 and AV100, respectively), and a DLR algorithm (TrueFidelity) with three strength levels (low, medium, and high). Noise power spectrum (NPS) and edge rise distance (ERD) were used to evaluate noise characteristics and spatial resolution, respectively. Image noise, edge definition, overall image quality, lesion detectability and conspicuity, and artifacts were qualitatively scored by two pediatric radiologists, and the scores of the two reviewers were averaged. A repeated-measures analysis of variance followed by the Bonferroni post-hoc test was used to compare NPS and ERD among the six reconstruction methods. The Friedman rank sum test followed by the Nemenyi-Wilcoxon-Wilcox all-pairs test was used to compare the results of the qualitative visual analysis among the six reconstruction methods. Results: The NPS noise magnitude of AV100 was significantly lower than that of the DLR, whereas the NPS peak of AV100 was significantly higher than that of the high- and medium-strength DLR (p < 0.001). The NPS average spatial frequencies were higher for DLR than for ASiR-V (p < 0.001). ERD was shorter with DLR than with ASiR-V and FBP (p < 0.001). Qualitative visual analysis revealed better overall image quality with high-strength DLR than with ASiR-V (p < 0.001). Conclusion: For pediatric abdominopelvic CT, the DLR algorithm may provide improved noise characteristics and better spatial resolution than the hybrid IR algorithm.

지능 최적 알고리즘을 이용한 전기임피던스 단층촬영법의 영상복원 (Intelligent Optimization Algorithm Approach to Image Reconstruction in Electrical Impedance Tomography)

  • 김호찬;부창친;이윤준
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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    • pp.513-516
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    • 2002
  • In electrical impedance tomography(EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents two intelligent optimization algorithm techniques such as genetic algorithm and simulated annealing for the solution of the static EIT inverse problem. We summarize the simulation results for the three algorithm forms: modified Newton-Raphson, genetic algorithm, and simulated annealing.

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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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    • 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.

Newly-designed adaptive non-blind deconvolution with structural similarity index in single-photon emission computed tomography

  • Kyuseok Kim;Youngjin Lee
    • 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.

무손실.손실 영상 압축을 위한 웨이브릿 기반 알고리즘에 관한 연구 (A Study on the Wavelet Based Algorithm for Lossless and Lossy Image Compression)

  • 안종구;추형석
    • 대한전기학회논문지:시스템및제어부문D
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    • 제55권3호
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    • pp.124-130
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    • 2006
  • A wavelet-based image compression system allowing both lossless and lossy image compression is proposed in this paper. The proposed algorithm consists of the two stages. The first stage uses the wavelet packet transform and the quad-tree coding scheme for the lossy compression. In the second stage, the residue image taken between the original image and the lossy reconstruction image is coded for the lossless image compression by using the integer wavelet transform and the context based predictive technique with feedback error. The proposed wavelet-based algorithm, allowing an optional lossless reconstruction of a given image, transmits progressively image materials and chooses an appropriate wavelet filter in each stage. The lossy compression result of the proposed algorithm improves up to the maximum 1 dB PSNR performance of the high frequency image, compared to that of JPEG-2000 algorithm and that of S+P algorithm. In addition, the lossless compression result of the proposed algorithm improves up to the maximum 0.39 compression rates of the high frequency image, compared to that of the existing algorithm.

DC offset을 보정한 나선 주사 초고속 자기공명영상의 재구성 알고리즘 (Improved Reconstruction Algorithm for Spiral Scan Fast MR Imaging with DC offset Correction)

  • 안창범;김휴정
    • 대한의용생체공학회:의공학회지
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    • 제19권3호
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    • pp.243-250
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    • 1998
  • 초고속 자기공명 영상 기법의 일종인 나선 주사 영상의 재구성을 위하여 k-공간에서 극좌표와 직각 좌표계를 기초로한 재구성방법들을 분석하였다. 나선 주사 영상의 재구성은 나선 궤적상에서 측정된 데이터를 극좌표나 직각 좌표계로 변환시키기 위하여 보간 기술들이 사용된다. 나선주사 영상의 다양한 재구성 알고리즘들을 시험하여 보았고, 재구성된 영상의 질을 비교하였다. 본 연구진이 제안한 투영 영역에서 dc-offset보정을 한 향상된 재구성 알고리즘이 시뮬레이션을 통하여 가장 우수한 것으로 나타났다. 또한, 기존의 재구성 방법들에서 나타났던 영상 artifact도 제안된 방법에서는 완전히 사라짐을 확인할 수 있었다.

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