Journal article
Nonlinear Microwave Imaging for Breast-Cancer Screening Using Gauss–Newton's Method and the CGLS Inversion Algorithm
Breast-cancer screening using microwave imaging is emerging as a new promising technique as a supplement to X-ray mammography. To create tomographic images from microwave measurements, it is necessary to solve a nonlinear inversion problem, for which an algorithm based on the iterative Gauss-Newton method has been developed at Dartmouth College.
This algorithm determines the update values at each iteration by solving the set of normal equations of the problem using the Tikhonov algorithm. In this paper, a new algorithm for determining the iteration update values in the Gauss-Newton algorithm is presented which is based on the conjugate gradient least squares (CGLS) algorithm.
The iterative CGLS algorithm is capable of solving the update problem by operating on just the Jacobian and the regularizing effects of the algorithm can easily be controlled by adjusting the number of iterations. The new algorithm is compared to the Gauss-Newton algorithm with Tikhonov regularization and is shown to reconstruct images of similar quality using fewer iterations.
| Language: | English |
|---|---|
| Publisher: | IEEE |
| Year: | 2007 |
| Pages: | 2320-2331 |
| ISSN: | 15582221 and 0018926x |
| Types: | Journal article |
| DOI: | 10.1109/TAP.2007.901993 |
Biomedical electromagnetic imaging Breast cancer CGLS inversion algorithm Gauss-Newton method Gaussian processes Iterative algorithms Least squares methods Microwave imaging Microwave theory and techniques Newton method Optical imaging Recursive estimation Tikhonov regularization X-ray imaging biomedical electromagnetic imaging biomedical imaging breast-cancer screening cancer conjugate gradient least squares algorithm conjugate gradient methods electromagnetic scattering inverse problems image reconstruction imaging inverse problems microwave imaging nonlinear equations nonlinear microwave imaging
