Microwave imaging-complex permittivity reconstruction-by simulated annealing

1991 ◽  
Vol 39 (11) ◽  
pp. 1801-1807 ◽  
Author(s):  
L. Garnero ◽  
A. Franchois ◽  
J.-P. Hugonin ◽  
C. Pichot ◽  
N. Joachimowicz
Keyword(s):  
Simulated Annealing ◽  
Complex Permittivity ◽  
Microwave Imaging

scholarly journals A Subspace Preconditioned LSQR Gauss-Newton Method with a Constrained Line Search Path Applied to 3D Biomedical Microwave Imaging

2015 ◽  
Vol 2015 ◽  
pp. 1-21
Author(s):  
Jürgen De Zaeytijd ◽  
Ann Franchois
Keyword(s):  
Complex Permittivity ◽  
Line Search ◽  
Synthetic Data ◽  
Iterative Solution ◽  
Initial Guess ◽  
Microwave Imaging ◽  
Single Frequency ◽  
Problem Solution ◽  
Source Position ◽  
Search Path

Three contributions that can improve the performance of a Newton-type iterative quantitative microwave imaging algorithm in a biomedical context are proposed. (i) To speed up the iterative forward problem solution, we extrapolate the initial guess of the field from a few field solutions corresponding to previous source positions for the same complex permittivity (i.e., “marching on in source position”) as well as from a Born-type approximation that is computed from a field solution corresponding to one previous complex permittivity profile for the same source position. (ii) The regularized Gauss-Newton update system can be ill-conditioned; hence we propose to employ a two-level preconditioned iterative solution method. We apply the subspace preconditioned LSQR algorithm from Jacobsen et al. (2003) and we employ a 3D cosine basis. (iii) We propose a new constrained line search path in the Gauss-Newton optimization, which incorporates in a smooth manner lower and upper bounds on the object permittivity, such that these bounds never can be violated along the search path. Single-frequency reconstructions from bipolarized synthetic data are shown for various three-dimensional numerical biological phantoms, including a realistic breast phantom from the University of Wisconsin-Madison (UWCEM) online repository.

scholarly journals On Microwave Breast Imaging with Ultrasound Spatial Priors

2020 ◽  
Author(s):  
Nozhan Bayat ◽  
Puyan Mojabi ◽  
Pedram Mojabi ◽  
Joe LoVetri
Keyword(s):  
Complex Permittivity ◽  
Breast Imaging ◽  
Structural Information ◽  
Microwave Imaging ◽  
Ultrasound Images ◽  
Post Processing ◽  
Main Approach ◽  
Imaging Algorithm ◽  
Microwave Breast Imaging ◽  
Microwave Image

We investigate the use of ultrasound images as prior structural information (also known as ultrasound spatial priors) to guide microwave breast imaging so as to enhance its achievable complex permittivity images. In the main approach considered herein, the edges within the discretized<br>ultrasound compressibility image are fed as spatial priors<br>into a microwave imaging algorithm. It is shown that this<br>method requires minimal post-processing of the ultrasound<br>image and can enhance the achievable microwave image<br>accuracy. It is also demonstrated that small tumours can<br>still go undetected in microwave breast imaging using this<br>method if their edges are missing from the spatial priors.

scholarly journals On Microwave Breast Imaging with Ultrasound Spatial Priors

2020 ◽  
Author(s):  
Nozhan Bayat ◽  
Puyan Mojabi ◽  
Pedram Mojabi ◽  
Joe LoVetri
Keyword(s):  
Complex Permittivity ◽  
Breast Imaging ◽  
Structural Information ◽  
Microwave Imaging ◽  
Ultrasound Images ◽  
Post Processing ◽  
Main Approach ◽  
Imaging Algorithm ◽  
Microwave Breast Imaging ◽  
Microwave Image

We investigate the use of ultrasound images as prior structural information (also known as ultrasound spatial priors) to guide microwave breast imaging so as to enhance its achievable complex permittivity images. In the main approach considered herein, the edges within the discretized<br>ultrasound compressibility image are fed as spatial priors<br>into a microwave imaging algorithm. It is shown that this<br>method requires minimal post-processing of the ultrasound<br>image and can enhance the achievable microwave image<br>accuracy. It is also demonstrated that small tumours can<br>still go undetected in microwave breast imaging using this<br>method if their edges are missing from the spatial priors.

scholarly journals Development of an Anthropomorphic Phantom of the Axillary Region for Microwave Imaging Assessment

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4968
Author(s):  
Matteo Savazzi ◽  
Soroush Abedi ◽  
Niko Ištuk ◽  
Nadine Joachimowicz ◽  
Hélène Roussel ◽  
...  
Keyword(s):  
Complex Permittivity ◽  
Current Knowledge ◽  
Conductive Polymer ◽  
Microwave Imaging ◽  
Good Representation ◽  
Axillary Lymph ◽  
Experimental Assessment ◽  
Imaging Technology ◽  
Axillary Region ◽  
3D Printed

We produced an anatomically and dielectrically realistic phantom of the axillary region to enable the experimental assessment of Axillary Lymph Node (ALN) imaging using microwave imaging technology. We segmented a thoracic Computed Tomography (CT) scan and created a computer-aided designed file containing the anatomical configuration of the axillary region. The phantom comprises five 3D-printed parts representing the main tissues of interest of the axillary region for the purpose of microwave imaging: fat, muscle, bone, ALNs, and lung. The phantom allows the experimental assessment of multiple anatomical configurations, by including ALNs of different size, shape, and number in several locations. Except for the bone mimicking organ, which is made of solid conductive polymer, we 3D-printed cavities to represent the fat, muscle, ALN, and lung and filled them with appropriate tissue-mimicking liquids. Existing studies about complex permittivity of ALNs have reported limitations. To address these, we measured the complex permittivity of both human and animal lymph nodes using the standard open-ended coaxial-probe technique, over the 0.5 GHz–8.5 GHz frequency band, thus extending current knowledge on dielectric properties of ALNs. Lastly, we numerically evaluated the effect of the polymer which constitutes the cavities of the phantom and compared it to the realistic axillary region. The results showed a maximum difference of 7 dB at 4 GHz in the electric field magnitude coupled to the tissues and a maximum of 10 dB difference in the ALN response. Our results showed that the phantom is a good representation of the axillary region and a viable tool for pre-clinical assessment of microwave imaging technology.

Microwave imaging method using a simulated annealing approach

1991 ◽  
Vol 1 (11) ◽  
pp. 331-333 ◽  
Author(s):  
S. Caorsi ◽  
G.L. Gragnani ◽  
S. Medicina ◽  
M. Pastorino ◽  
G. Zunino
Keyword(s):  
Simulated Annealing ◽  
Microwave Imaging ◽  
Imaging Method
Sign in / Sign up

Export Citation Format

Share Document