Multimodal medical image fusion based on joint bilateral filter and local gradient energy

Li, Xiaosong; Zhou, Fuqiang; Tan, Haishu; Zhang, Wanning; Zhao, Congyang

doi:10.1016/j.ins.2021.04.052

Cited by 101 publications

(34 citation statements)

References 43 publications

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“…e fused image can be reconstructed by the perfused highfrequency, low-frequency structure, and low-frequency texture. In literature [24], an effective, fast, and robust medical image fusion method is proposed. A two-layer decomposition scheme is introduced by the joint bilateral filter, the energy layer contains rich intensity information, and the structure layer captures ample details.…”

Section: Texture Inpainting Methodmentioning

confidence: 99%

A Criminisi-DnCNN Model-Based Image Inpainting Method

Zhu

Wang

2022

Mathematical Problems in Engineering

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Existing image inpainting methods achieve unideal results in dealing with centralized inpainting areas. For this reason, in this study, a Criminisi-DnCNN model-based image inpainting method is proposed. Inspired by the manual inpainting technology, the pointwise mutual information (PMI) algorithm was adopted to obtain the marginal structural map of the images to be repaired. Then, the Criminisi algorithm was used to restore the marginal structure to obtain the complete marginal structure image guided by the superficial linear structure. Finally, the problem of texture inpainting was converted into the counterpart of image denoising through the separation of variables by using the denoising convolutional neural network image denoiser (DnCNN). Compared with the existing inpainting methods, this model has improved the clarity of the marginal structure and reduced the blurring of the area to be repaired.

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Section: Texture Inpainting Methodmentioning

confidence: 99%

A Criminisi-DnCNN Model-Based Image Inpainting Method

Zhu

Wang

2022

Mathematical Problems in Engineering

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“…Similar to other filtering principles, bilateral filtering also uses the weighted average method. The weighted average of the brightness value of the surrounding pixels represents the strength of a certain pixel, and the weighted average is based on Gaussian distribution [47,48]. However, the weight of bilateral filtering not only considers the Euclidean distance of the pixel-core (such as Gaussian filtering) domain, but also considers the radiation difference (such as the similarity between the pixel and the central pixel) value domain in the pixel range domain.…”

Section: Considering the Computational Domainmentioning

confidence: 99%

“…Therefore, The numerical comparison results show that ARIMA predicts the variable force relatively well. The prediction result was F2 by the ARIMA algorithm, and then according to the energy equation and variational principle, it is easy to obtain the equilibrium equation [48][49][50]. In Example 2, the corresponding stress, strain and displacement cloud are calculated under t = 10.82 s and predictive force F2 = 2194.1522 N. The solution process is the same as Section 2.…”

Section: Examplementioning

confidence: 99%

ARIMA-FEM Method with Prediction Function to Solve the Stress–Strain of Perforated Elastic Metal Plates

Chen

Dai

Zheng

2022

Metals

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Stress analysis and deformation prediction have always been the focuses of the field of mechanics. The accurate force prediction in plate deformation plays important role in the production, processing and performance analysis of materials. In this paper, we propose an ARIMA-FEM method, which can be used to solve some mechanical problems of 2D porous elastic plate. We have given a detailed theory and solving steps of ARIMA-FEM. In addition, three numerical examples are given to predict the stress–strain of thin porous elastic metal plates. This article uses CST, LST and Q4 elements to discrete the rectangular plates, square plates and circle plates with holes. As for variable force prediction, this paper compared with linear regression, nonlinear regression and neural network prediction, and the results show that the ARIMA method has a higher prediction accuracy. Furthermore, we calculate the numerical solution at four mesh scales, and the numerical convergence is consistent with the theoretical convergence, which also shows the effectiveness of our method. The image smoothing algorithm is applied to keep edge information with high resolution, which can more concisely describe the plate internal changes. Finally, the application scope of ARIMA-FEM, model expansion, superconvergence analysis and other issues have been given enlightening views in the discussion section. In fact, this algorithm combined statistics and mechanics. It also reflects the knowledge integration of interdisciplinary and uses it better to serve practical applications.

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“…Where w(i,j,k,l) describes spatial domain kernel template weight, w s (i,j,k,l) describes value domain kernel template weight, w r (i,j,k,l) describes bilateral lter template weight, (i,j) describes the position of the relevant pixel around the target pixel, f(i,j) represents pixel value, (k,l) represents the position of the target pixel, f (k,l) represents the pixel value of the target pixel, {\text{σ}}_{\text{s}} is distance standard deviation of Gaussian function, {\text{σ}}_{\text{r}} is gray standard deviation of Gaussian function [43].…”

Section: The Pixel Weight Calculation On the Graph Variable Edgementioning

confidence: 99%

Knots searching and location of Chinese Fir (Cunninghamia lanceolata(lamb.) hook) constructional lumber from Fujian province, China: using contour fitting and extraction method

Zhang

et al. 2022

Preprint

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This study focuses on studying knots searching and location of Fujian Chinese Fir(FCF) constructional lumber(CL), Combining with the surface characteristics of FCF, a method for locating defects in the knots of FCF CL was developed. Combining with the surface characteristics of FCF CL, searching and locating the knots position at the trough of the profile line. The effect of knot in different position on the modulus of elasticity and the bending strength of FCF CL was studied by mechanical testing machine. This method can be used to calculate the surface defects of lumber quickly and comprehensively, so as to achieve the classification and evaluation of FCF CL according to the standard. This study is of great significance in intelligent detection, efficient production and full utilization of CL, and promotes the safe, stable and green application and development of building materials.

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Multimodal medical image fusion based on joint bilateral filter and local gradient energy

Cited by 101 publications

References 43 publications

A Criminisi-DnCNN Model-Based Image Inpainting Method

A Criminisi-DnCNN Model-Based Image Inpainting Method

ARIMA-FEM Method with Prediction Function to Solve the Stress–Strain of Perforated Elastic Metal Plates

Knots searching and location of Chinese Fir (Cunninghamia lanceolata(lamb.) hook) constructional lumber from Fujian province, China: using contour fitting and extraction method

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