Proceedings of the 2019 International Conference on Modeling, Simulation, Optimization and Numerical Techniques (SMONT 2019)

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Total Variation Minimization Enhanced Quantitative Microwave Induced Thermoacoustic Tomography using a GPU-accelerated Finite Element Method

Authors
Yunchao Jiang, Zhu Zheng, Min Wang, Lei Yao
Corresponding Author
Lei Yao
Available Online April 2019.
DOI
10.2991/smont-19.2019.43How to use a DOI?
Keywords
thermoacoustic tomography; total variation minimization; finite element method; GPU acceleration
Abstract

Microwave induced thermoacoustic tomography (MI-TAT) combines the advantages of microwave imaging and ultrasound imaging to obtain high-resolution and high-contrast biological tissue microwave energy absorption images. However, the current MI-TAT technique often gets images with a large number of artifacts or error results in the case of small number of sensors and limited detection angle. In this paper, we first introduction the total variation minimization (TVM) in the field of finite element method (FEM) based MI-TAT reconstruction algorithm and we can get perfect thermoacoustic image reconstruction with a small number of detectors and limited-angles. Since this approach is extremely computationally demanding, we apply the parallel strategy using a multi-core graphic-processing-unit (GPU) card to accelerate the calculation. The improved algorithm is verified and evaluated through simulations and phantom experiments, and the results suggest that our new method holds great potential in various clinical studies in the future.

Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2019 International Conference on Modeling, Simulation, Optimization and Numerical Techniques (SMONT 2019)
Series
Advances in Intelligent Systems Research
Publication Date
April 2019
ISBN
10.2991/smont-19.2019.43
ISSN
1951-6851
DOI
10.2991/smont-19.2019.43How to use a DOI?
Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - CONF
AU  - Yunchao Jiang
AU  - Zhu Zheng
AU  - Min Wang
AU  - Lei Yao
PY  - 2019/04
DA  - 2019/04
TI  - Total Variation Minimization Enhanced Quantitative Microwave Induced Thermoacoustic Tomography using a GPU-accelerated Finite Element Method
BT  - Proceedings of the 2019 International Conference on Modeling, Simulation, Optimization and Numerical Techniques (SMONT 2019)
PB  - Atlantis Press
SP  - 189
EP  - 193
SN  - 1951-6851
UR  - https://doi.org/10.2991/smont-19.2019.43
DO  - 10.2991/smont-19.2019.43
ID  - Jiang2019/04
ER  -