Image restoration algorithm incorporating methods to remove noise and blurring from positron emission tomography imaging for Alzheimer's disease diagnosis

Lee, Minhee; Yun, Chang‐Soo; Kim, Kyuseok; Lee, Youngjin

doi:10.1016/j.ejmp.2022.10.016

Cited by 9 publications

(4 citation statements)

References 61 publications

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“…where Q is the set of feasible I MG 2 , PSF σ ⊗ ⊗I MG 2 − I MG 2 is the fidelity term, ∇I MG 2 is the regularization term, and λ is the balancing factor due to control of the signal-to-noise ratio (i.e., λ = 0.01 was used in this study). Here, the regularization term was set to the total variation-based l 1 -norm calculation to avoid artifacts [44,48]. The solving method to find the f * used the augmented Lagrangian of the problem technique [60], and the tolerance used 1 × 10 −4 with an iteration loop stop condition.…”

Section: Proposed Restoration Framework Based On the Adaptive Psf Est...mentioning

confidence: 99%

“…However, TV-and TGV-based regulationterm methods often tend to produce staircase artifacts [47]. Another approach is the deconvolution method after the noise reduction process, where deconvolution is performed considering the total PSF, composed of blurring in the imaging system and smoothing of the noise reduction algorithm [48]. This method can minimize noise amplification during deconvolution by removing the noise.…”

Section: Introductionmentioning

confidence: 99%

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Development of Adaptive Point-Spread Function Estimation Method in Various Scintillation Detector Thickness for X-ray Imaging

Cha,

Lee,

Kim

2023

Sensors

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An indirect conversion X-ray detector uses a scintillator that utilizes the proportionality of the intensity of incident radiation to the amount of visible light emitted. A thicker scintillator reduces the patient’s dose while decreasing the sharpness. A thin scintillator has an advantage in terms of sharpness; however, its noise component increases. Thus, the proposed method converts the spatial resolution of radiographic images acquired from a normal-thickness scintillation detector into a thin-thickness scintillation detector. Note that noise amplification and artifacts were minimized as much as possible after non-blind deconvolution. To accomplish this, the proposed algorithm estimates the optimal point-spread function (PSF) when the structural similarity index (SSIM) and feature similarity index (FSIM) are the most similar between thick and thin scintillator images. Simulation and experimental results demonstrate the viability of the proposed method. Moreover, the deconvolution images obtained using the proposed scheme show an effective image restoration method in terms of the human visible system compared to that of the traditional PSF measurement technique. Consequently, the proposed method is useful for restoring degraded images using the adaptive PSF while preventing noise amplification and artifacts and is effective in improving the image quality in the present X-ray imaging system.

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Section: Proposed Restoration Framework Based On the Adaptive Psf Est...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development of Adaptive Point-Spread Function Estimation Method in Various Scintillation Detector Thickness for X-ray Imaging

Cha,

Lee,

Kim

2023

Sensors

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“…The factors that analyze the form of natural scene statistics in the acquired medical image are NIQE and BRISQUE evaluation parameters, and the principle of deriving these values is to analyze the degree of distortion of the shape of the Gaussian curve. In particular, NIQE and BRISQUE can be used as a method to comprehensively analyze the decrease in the spatial resolution or sharpness of medical images that inevitably occurs depending on the denoising method [35]. Accordingly, we expect that the above no-reference-based evaluation methods can be used as indicators to confirm the performance of segmentation using the MMWF technology.…”

Section: Discussionmentioning

confidence: 99%

Optimization of Median Modified Wiener Filter for Improving Lung Segmentation Performance in Low-Dose Computed Tomography Images

Lim,

Park,

Kim

et al. 2023

Applied Sciences

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In low-dose computed tomography (LDCT), lung segmentation effectively improves the accuracy of lung cancer diagnosis. However, excessive noise is inevitable in LDCT, which can decrease lung segmentation accuracy. To address this problem, it is necessary to derive an optimized kernel size when using the median modified Wiener filter (MMWF) for noise reduction. Incorrect application of the kernel size can result in inadequate noise removal or blurring, degrading segmentation accuracy. Therefore, various kernel sizes of the MMWF were applied in this study, followed by region-growing-based segmentation and quantitative evaluation. In addition to evaluating the segmentation performance, we conducted a similarity assessment. Our results indicate that the greatest improvement in segmentation performance and similarity was at a kernel size 5 × 5. Compared with the noisy image, the accuracy, F1-score, intersection over union, root mean square error, and peak signal-to-noise ratio using the optimized MMWF were improved by factors of 1.38, 33.20, 64.86, 7.82, and 1.30 times, respectively. In conclusion, we have demonstrated that by applying the MMWF with an appropriate kernel size, the optimization of noise and blur reduction can enhance segmentation performance.

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“…The low-resolution image of the thick scintillation detector was restored to its optimal resolution using the optimal PSFs (PSF L , PSF H , PSF V , and PSF D ). As a non-blind deconvolution method, we used the l 1 -norm-based total variation (TV) minimization in Equation ( 4), which was shown to be effective in terms of artifact suppression in previous studies [30,31].…”

Section: Proposed Optimal Deblurring Frameworkmentioning

confidence: 99%

Investigation of Deconvolution Method with Adaptive Point Spread Function Based on Scintillator Thickness in Wavelet Domain

Kim,

Cha,

Jeong

et al. 2024

Bioengineering

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In recent years, indirect digital radiography detectors have been actively studied to improve radiographic image performance with low radiation exposure. This study aimed to achieve low-dose radiation imaging with a thick scintillation detector while simultaneously obtaining the resolution of a thin scintillation detector. The proposed method was used to predict the optimal point spread function (PSF) between thin and thick scintillation detectors by considering image quality assessment (IQA). The process of identifying the optimal PSF was performed on each sub-band in the wavelet domain to improve restoration accuracy. In the experiments, the edge preservation index (EPI) values of the non-blind deblurred image with a blurring sigma of σ = 5.13 pixels and the image obtained with optimal parameters from the thick scintillator using the proposed method were approximately 0.62 and 0.76, respectively. The coefficient of variation (COV) values for the two images were approximately 1.02 and 0.63, respectively. The proposed method was validated through simulations and experimental results, and its viability is expected to be verified on various radiological imaging systems.

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Image restoration algorithm incorporating methods to remove noise and blurring from positron emission tomography imaging for Alzheimer's disease diagnosis

Cited by 9 publications

References 61 publications

Development of Adaptive Point-Spread Function Estimation Method in Various Scintillation Detector Thickness for X-ray Imaging

Development of Adaptive Point-Spread Function Estimation Method in Various Scintillation Detector Thickness for X-ray Imaging

Optimization of Median Modified Wiener Filter for Improving Lung Segmentation Performance in Low-Dose Computed Tomography Images

Investigation of Deconvolution Method with Adaptive Point Spread Function Based on Scintillator Thickness in Wavelet Domain

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