Denoising Method for Passive Photon Counting Images Based on Block-Matching 3D Filter and Non-Subsampled Contourlet Transform

Wang, Xuan; Yin, Lu; Gao, Mingliang; Wang, Zhenzhou; Shen, Jin; Zou, Guofeng

doi:10.3390/s19112462

Cited by 10 publications

(5 citation statements)

References 33 publications

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“…The filtered back projection (FBP) reconstruction algorithm [ 18 ], total variation minimization (TV algorithm) [ 19 ], and block-matched three-dimensional filtering (BM3D algorithm) [ 20 ] were introduced. The normalized mean absolute distance (NMAD), root mean square error (RMSE), structural similarity index measure (SSIM), and peak signal to noise ratio (PSNR) were compared to evaluate the noise reduction effect of the model.…”

Section: Methodsmentioning

confidence: 99%

Effect Evaluation of Platelet-Rich Plasma Combined with Vacuum Sealing Drainage on Serum Inflammatory Factors in Patients with Pressure Ulcer by Intelligent Algorithm-Based CT Image

Yang

Xiao

Wen

et al. 2022

Computational and Mathematical Methods in Medicine

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This work was to explore the efficacy of intelligent algorithm-based computed tomography (CT) to evaluate platelet-rich plasma (PRP) combined with vacuum sealing drainage (VSD) in the treatment of patients with pressure ulcers. Based on the u-net network structure, an image denoising algorithm based on double residual convolution neural network (Dr-CNN) was proposed to denoise the CT images. A total of 84 patients who were hospitalized in hospital were randomly divided into group A (without any intervention), group B (PRP treatment), group C (VSD treatment), and group D (PRP+VSD treatment). Procalcitonin (PCT) was detected by enzyme-linked immunosorbent assay (ELISA) combined with immunofluorescence method, C-reactive protein (CRP) was detected by rate reflectance turbidimetry (RRT), and interleukin-6 (IL-6) was detected by electrochemiluminescence method. The results showed that after treatment, 44 cases (52.38%) of pressure ulcers patients recovered, 24 cases (28.57%) had no change in stage, and 16 cases (19.04%) developed pressure ulcers. The pain scores of group D at 1 week ( 3.35 ± 0.56 points) and 2 weeks ( 2.76 ± 0.55 points) after treatment were significantly lower than those in group C ( 7.77 ± 0.58 points and 6.34 ± 0.44 points, respectively). The time of complete wound healing in group D ( 24.5 ± 2.32 ) was obviously lower in contrast to that in groups A, B, and C ( 35.54 ± 3.22 days, 30.23 ± 2 days, and 29.34 ± 2.15 days, respectively). In addition, the medical satisfaction of group D ( 8.74 ± 0.69 ) was significantly higher than that of groups A, B, and C ( 4.69 ± 0.85 , 5.22 ± 0.31 , and 5.18 ± 0.59 , respectively). The levels of IL-6 and PCT in group D were lower than those in groups A, B, and C, and the differences were statistically significant ( P < 0.01 ). The average values of peak signal to noise ratio (PSNR) and structural similarity index measure (SSIM) of the Dr-CNN network model were 37.21 ± 1.09 dB and 0.925 ± 0.01 , respectively, which were higher than other algorithms. The mean values of root mean square error (MSE) and normalized mean absolute distance (NMAD) of the Dr-CNN network model were 0.022 ± 0.002 and 0.126 ± 0.012 , respectively, which were significantly lower than other algorithms ( P < 0.05 ). The experimental results showed that PrP combined with VSD could significantly reduce the inflammatory response of patients with pressure ulcers. PRP combined with VSD could significantly reduce the pain of dressing change for patients. Moreover, the performance model of image denoising algorithm based on double residual convolutional neural network was better than other algorithms.

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Section: Methodsmentioning

confidence: 99%

Effect Evaluation of Platelet-Rich Plasma Combined with Vacuum Sealing Drainage on Serum Inflammatory Factors in Patients with Pressure Ulcer by Intelligent Algorithm-Based CT Image

Yang

Xiao

Wen

et al. 2022

Computational and Mathematical Methods in Medicine

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“…(1) Generate an Initial Population. Real number coding is used as the coding scheme, and real number coding is highly effective for function optimization problems [22]. Generate the initial population, set the adaptive threshold range to [0.5, 0.8], randomly generate a population uniformly distributed in this range, denoted by fη 1 , η 2 ,⋯,η N g, and select the optimal η i to maximize the information entropy of the denoised image.…”

Section: Genetic Algorithm Optimizes Thresholdmentioning

confidence: 99%

An NSCT Image Denoising Method Based on Genetic Algorithm to Optimize the Threshold

Zhang

Wang

et al. 2022

Mobile Information Systems

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In order to solve the defect that the threshold value of the NSCT transform method is too large or the real signal coefficients are directly lost during image denoising, an adaptive threshold method of genetic algorithm is used to optimize the NSCT image denoising method. The genetic algorithm is used to generate the initial population, and the genetic operator is determined by selection, crossover, and mutation operations to achieve NSCT threshold optimization. The obtained optimized NSCT threshold is used to process different directions. The coefficients of different scales are processed by using NSCT inverse transform to obtain the denoised image. The results of the case analysis show that the proposed method is used to denoise the image, the peak signal-to-noise ratio of the image after denoising is higher than 30 dB, the image contains rich edge information and detailed information, and the denoising performance is superior.

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“…However, a lock-in-amplifier cannot be synchronized to multiple pixels resulting in a significant reduction in SNR as compared to scanned approach [5]. Finally, scattering is a concern for THz systems.…”

Section: Related Work and The General Noisementioning

confidence: 99%

Denoising Terahertz Image Using Non-Linear Filters

2021

CEIS

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A major challenge in the processing and analysis of images is the presence of noise especially in terahertz images. Denoising techniques are designed to remove noise or distorted images while maintaining the original image quality. In this paper, terahertz image denoising is proposed using different filtering methods. This work provides an algorithm that denotes the terahertz image with a non-linear and spatial function of mean and medium filter. The THz images were transformed using Gaussian and Salt & Pepper noise at different percentage levels from 5% to 50%. Universal Image Quantitative Analysis was utilized specifically the most renowned PSNR, MSE, MAE and IEF were explored in this work. Experimental results show that the mean-median filter outperforms Salt and Pepper in removing the Gaussian noise especially when noise factor is increasing.

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Denoising Method for Passive Photon Counting Images Based on Block-Matching 3D Filter and Non-Subsampled Contourlet Transform

Cited by 10 publications

References 33 publications

Effect Evaluation of Platelet-Rich Plasma Combined with Vacuum Sealing Drainage on Serum Inflammatory Factors in Patients with Pressure Ulcer by Intelligent Algorithm-Based CT Image

Effect Evaluation of Platelet-Rich Plasma Combined with Vacuum Sealing Drainage on Serum Inflammatory Factors in Patients with Pressure Ulcer by Intelligent Algorithm-Based CT Image

An NSCT Image Denoising Method Based on Genetic Algorithm to Optimize the Threshold

Denoising Terahertz Image Using Non-Linear Filters

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