Fast Microwave Tomography Algorithm for Breast Cancer Imaging
Doktorsavhandling, 2021

Microwave tomography has shown promise for breast cancer imaging. The microwaves are harmless to body tissues, which makes microwave tomography a safe adjuvant screening to mammography. Although many clinical studies have shown the effectiveness of regular screening for the detection of breast cancer, the anatomy of the breast and its critical tissues challenge the identification and diagnosis of tumors in this region. Detection of tumors in the breast is more challenging in heterogeneously dense and extremely dense breasts, and microwave tomography has the potential to be effective in such cases. The sensitivity of microwaves to various breast tissues and the comfort and safety of the screening method have made microwave tomography an attractive imaging technique.
Despite the need for an alternative screening technique, microwave tomography has not yet been introduced as a screening modality in regular health care, and is still subject to research. The main obstacles are imperfect hardware systems and inefficient imaging algorithms. The immense computational costs for the image reconstruction algorithm present a crucial challenge. 2D imaging algorithms are proposed to reduce the amount of hardware resources required and the imaging time. Although 2D microwave tomography algorithms are computationally less expensive, few imaging groups have been successful in integrating the acquired 3D data into the 2D tomography algorithms for clinical applications.
The microwave tomography algorithms include two main computation problems: the forward problem and the inverse problem. The first part of this thesis focuses on a new fast forward solver, the 2D discrete dipole approximation (DDA), which is formulated and modeled. The effect of frequency, sampling number, target size, and contrast on the accuracy of the solver are studied. Additionally, the 2D DDA time efficiency and computation time as a single forward solver are investigated.  The second part of this thesis focuses on the inverse problem. This portion of the algorithm is based on a log-magnitude and phase transformation optimization problem and is formulated as the Gauss-Newton iterative algorithm. The synthetic data from a finite-element-based solver (COMSOL Multiphysics) and the experimental data acquired from the breast imaging system at Chalmers University of Technology are used to evaluate the DDA-based image reconstruction algorithm. The investigations of modeling and computational complexity show that the 2D DDA is a fast and accurate forward solver that can be embedded in tomography algorithms to produce images in seconds. The successful development and implementation in this thesis of 2D tomographic breast imaging with acceptable accuracy and high computational cost efficiency has provided significant savings in time and in-use memory and is a dramatic improvement over previous implementations.

inverse problem

forward solver

breast cancer

discrete dipole approximation

microwave tomography

computational cost

Jacobian matrix

Online
Opponent: Prof. Ari Sihvola, Aalto University, Finland

Författare

Samar Hosseinzadegan

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik, Biomedicinsk elektromagnetik

Application of two-dimensional discrete dipole approximation in simulating electric field of a microwave breast imaging system

IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology,; Vol. 3(2019)p. 80-87

Artikel i vetenskaplig tidskrift

A discrete dipole approximation solver based on the COCG-FFT algorithm and its application to microwave breast imaging

International Journal of Antennas and Propagation,; Vol. 2019(2019)

Artikel i vetenskaplig tidskrift

Samar Hosseinzadegan, Andreas Fhager, Mikael Persson, Shireen Geimer, and Paul Meaney, Discrete Dipole Approximation-Based Microwave Tomography for Fast Breast Cancer Imaging.

Cancer is recognized as a dominant cause of fatalities worldwide. The World Health Organization (WHO) has reported breast cancer as the most common cancer in women. WHO has also recently noted a growth in breast cancer cases due to contemporary lifestyles. Implementation of prevention policies together with early detection has been found highly effective in reducing the cancer burden. Many cancers are curable if they are diagnosed in the early stages and treated while the tumors are small.
The key to increasing the chance of survival in breast cancer is regular monitoring. For breast cancer imaging applications, the devices should be designed to be portable, cost effective, sensitive to various tissue types, user-friendly, harmless and comfortable for patients. Microwave technology has a great potential to meet these requirements, but it is still being developed, and has not yet been fully translated to the clinical setting. The benefit of a non-ionizing technique that does not require breast compression is particularly appealing for patient safety and comfort. Developing such imaging devices will require developing a fast and accurate electromagnetic solver.
The thesis focuses on the microwave tomography technique for fast breast cancer imaging. It is devoted to investigating the computational aspects and to addressing the heavy computational burden of microwave tomographic reconstruction algorithms. Two-dimensional (2D) images of breasts are obtained in a few seconds. The work is validated with both simulated and measured data. These 2D results are an important piece of the puzzle for simplifying and reducing system size, cost, and speed towards eventual deployment in under-resourced environments which are currently not able to establish conventional breast screening programs.

Styrkeområden

Hälsa och teknik

Ämneskategorier

Elektroteknik och elektronik

ISBN

978-91-7905-449-6

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4916

Utgivare

Chalmers tekniska högskola

Online

Online

Opponent: Prof. Ari Sihvola, Aalto University, Finland

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Senast uppdaterat

2021-02-15