• International Journal of Control, Automation, and Systems
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• v.3 no.2
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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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.2
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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.

• Journal of Biomedical Engineering Research
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• v.17 no.4
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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.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.1
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• pp.21-28
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• 2005

In this paper, we studied resolution to the FBP(Filtered Back-Propagation) tomographic image reconstruction algorithms. In order to analyze the resolution to the tomographic images, we derived ambiguity function to this algorithm which can be reconstructed from the improved FBP image reconstruction algorithm by using fixed coordinate system practically. Through simulation using this function, we determined the lateral and depth resolution quantitively and then analyzed respectively. Simulation results show that the lateral and depth resolution to the improved FBP image reconstruction algerian was determined $0.27\lambda\;and\;0.70\lambda$ at the 3dB, and also $0.89\lambda\;and\;0.96\lambda$ at the 6dB respectively. This results proved that improved FBP reconstruction algorithms for diffraction tomography of incident planar wave is useful to developed the tomographic image system, analyze the resolution to the tomographic images, we derived ambiguity function to this algerian which can be reconstructed from the improved FBP image reconstruction algorithm by using fixed coordinate system.

• Korean Journal of Radiology
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• v.23 no.7
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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.

• Proceedings of the KIEE Conference
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• 2002.11c
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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.

• 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.

• Nuclear Engineering and Technology
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• v.55 no.12
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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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.3
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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.

• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.243-250
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• 1998

Reconstruction aspects of spiral scan imaging for ultra fast magnetic resonance imagine(MRI) have been investigated with polar and rectangular coordinates-based reconstruction. For the reconstruction of the spiral scan imaging, acquired data in spiral trjectory should be converted to polar or rectangular grids, where interpolation techniques are used. Various reconstruction algorithms for spiral scan imaging are tested, and reconstructed image qualities are compared with computed phantom. An improved reconstruction algorithm with dc-offset correction in projection domain is proposed, which provides the best reconstructed image quality from the simulation. Image artifact with existing algorithms is completely removed with the proposed method.