Premium
Optimal microwave breast imaging using quality metrics and simulated annealing algorithm
Author(s) -
Xiao Xia,
Liu Yu,
Song Hang,
Kikkawa Takamaro
Publication year - 2020
Publication title -
international journal of rf and microwave computer‐aided engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.335
H-Index - 39
eISSN - 1099-047X
pISSN - 1096-4290
DOI - 10.1002/mmce.22364
Subject(s) - microwave imaging , image quality , imaging phantom , simulated annealing , microwave , breast imaging , computer science , clutter , algorithm , permittivity , metric (unit) , materials science , dielectric , breast cancer , artificial intelligence , optics , mammography , image (mathematics) , physics , telecommunications , medicine , optoelectronics , radar , engineering , operations management , cancer
Microwave breast imaging exploits dielectric contrasts between cancerous and healthy tissues at microwave frequencies to detect breast tumors. The estimation of breast optimal effective dielectric properties has a significant influence on the image quality. Recently, a novel method based on focal quality metrics (FQMs) has been proposed to investigate the patient‐specific effective dielectric properties. Although FQMs can be used to estimate the effective permittivity, the small increment of permittivity during the imaging process may lead to large computational resource consumption. In this article, an optimized microwave breast imaging method is proposed. In this method, a hybrid image quality metric is put forward which mixes the signal‐to‐clutter ratio (SCR) and focal quality metric. In addition, the simulated annealing algorithm is incorporated to facilitate image reconstruction. Experimental results demonstrate that using the proposed method, SCR is improved by 0.2 dB and tumor location error is reduced by 3.5 mm in realistic breast phantom.