Name
Abstract | ||
|---|---|---|
Microwave imaging (MWI) is an emerging tool for medical diagnostics, potentially offering unique advantages such as the capability of providing quantitative images of the inspected tissues. This involves, however, solving a challenging non-linear and ill-posed electromagnetic inverse scattering problem. This paper presents a robust method for quantitative microwave imaging in medical applications where very little, if any, a priori information on the imaging scenario is available. This is accomplished by employing a distorted Born iterative method (DBIM) and a regularization by projection technique, which reconstructs the tissue parameters using a wavelet basis expansion to represent the unknown contrast. This approach is suited for any microwave medical imaging application where the requirement for increased resolution dictates the use of higher frequency data, and consequently, a robust regularization strategy. To demonstrate the robustness of the proposed approach, the paper presents reconstructions of highly heterogeneous anatomically realistic numerical breast phantoms in a canonical two-dimensional (2-D) configuration. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/TBME.2014.2381270 | IEEE transactions on bio-medical engineering |
Keywords | Field | DocType |
quantitative mwi,electromagnetic scattering inverse problem,microwave medical imaging,wavelet transforms,robust regularization strategy,tissue parameter,wavelet-based regularization,distorted born inversion method (dbim),robust microwave imaging,projection technique,electromagnetic wave scattering,wavelet transform,distorted born iterative method,2d configuration,biological tissues,wavelet basis expansion,medical imaging,breast phantoms,microwave imaging,microwave imaging (mwi),phantoms,iterative methods,medical image processing,reconstruction,image reconstruction,tomography,strategies,cancer,inverse scattering,dielectric properties,inverse problems,robustness | Iterative reconstruction,Computer vision,Iterative method,Medical imaging,Computer science,Robustness (computer science),Artificial intelligence,Microwave imaging,Inverse problem,Wavelet transform,Wavelet | Journal |
Volume | Issue | ISSN |
62 | 4 | 0018-9294 |
Citations | PageRank | References |
3 | 0.43 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rosa Scapaticci | 1 | 27 | 3.96 |
| Panagiotis Kosmas | 2 | 11 | 1.23 |
| Lorenzo Crocco | 3 | 97 | 15.77 |