Diffusion optical tomography reconstruction based on convex–nonconvex graph total variation regularization-Reference-Cited by-同舟云学术

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Diffusion optical tomography reconstruction based on convex–nonconvex graph total variation regularization

Published:2022-10-05 Issue:4 Volume:46 Page:4534-4545
ISSN:0170-4214
Container-title:Mathematical Methods in the Applied Sciences
language:en
Short-container-title:Math Methods in App Sciences

Author:

Li Jinlan¹,Xie Zhaoyang¹,Liu Guoqi²,Yang Liu³,Zou Jian¹^ORCID

Affiliation:

1. School of Information and Mathematics Yangtze University Jingzhou China

2. College of Computer and Information Engineering Henan Normal University Xinxiang China

3. School of Computer Sciences and Cyber Engineering Guangzhou University Guangzhou China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

General Engineering,General Mathematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mma.8777

Reference44 articles.

1. Shape recovery for sparse-data tomography

2. Back-propagation neural network-based reconstruction algorithm for diffuse optical tomography

3. Accelerated Structure-Aware Sparse Bayesian Learning for Three-Dimensional Electrical Impedance Tomography

4. Efficient Multitask Structure-Aware Sparse Bayesian Learning for Frequency-Difference Electrical Impedance Tomography

5. Diffuse optical reconstructions of functional near infrared spectroscopy data using maximum entropy on the mean

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1. An MTL1TV non-convex regularization model for MR Image reconstruction using the alternating direction method of multipliers;Electronic Research Archive;2024

2. Mathematical and numerical challenges in diffuse optical tomography inverse problems;Discrete and Continuous Dynamical Systems - S;2024

3. Plug‐and‐play algorithms for convex non‐convex regularization: Convergence analysis and applications;Mathematical Methods in the Applied Sciences;2023-10-05

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