Parameter Search Algorithms for Microwave Radar-Based Breast Imaging: Focal Quality Metrics as Fitness Functions

Abstract

Inaccurate estimation of average dielectric properties can have a tangible impact on microwave radar-based breast images. Despite this, recent patient imaging studies have used a fixed estimate although this is known to vary from patient to patient. Parameter search algorithms are a promising technique for estimating the average dielectric properties from the reconstructed microwave images themselves without additional hardware. In this work, qualities of accurately reconstructed images are identified from point spread functions. As the qualities of accurately reconstructed microwave images are similar to the qualities of focused microscopic and photographic images, this work proposes the use of focal quality metrics for average dielectric property estimation. The robustness of the parameter search is evaluated using experimental dielectrically heterogeneous phantoms on the three-dimensional volumetric image. Based on a very broad initial estimate of the average dielectric properties, this paper shows how these metrics can be used as suitable fitness functions in parameter search algorithms to reconstruct clear and focused microwave radar images.

Optimal microwave breast imaging using quality metrics and simulated annealing algorithm

“…Lavoie et al 45 proposed a method to reconstruct microwaveradar breast images, where the optimal effective permittivity is estimated by a polynomial interpolant of fitness function. O'Loughlin et al 26 proposed a novel algorithm based on focal quality metrics, which is used to estimate the patient-specific average dielectric properties to reconstruct clear and focused microwave radar images. Oloumi et al 46 put forward a sectional image reconstruction method for compensating the different group speeds in various tissue-mimic layers.…”

“…2.1 | Proposed image metric factor 2.1.1 | The signal-to-clutter ratio SCR is generally used to evaluate image quality. In reference, 26 SCR of the reconstructed image is employed to assess the suitability of metrics for estimating average dielectric properties. In reference, 27 the background suppression performance is evaluated by SCR calculation to improve the detection ability of small targets in infrared image.…”

“…Recently, a method based on focal quality metrics (FQMs) has been proposed to estimate the effective permittivity. 25,26 In this method, the FQMs are utilized to assess the image quality and to investigate the patientspecific effective dielectric properties.…”

Comparing Radar-Based Breast Imaging Algorithm Performance with Realistic Patient-Specific Permittivity Estimation

“…Next, an assumed estimate of the relative permittivity of the breast was used to synthetically focus all signals to a point of interest within the breast [23]. Considering the generic radar-based beamformer shown in Equation (1), this is discretized and simplified to become the DAS beamformer in the frequency domain:…”

“…A more exhaustive comparative study using five clinical case studies identified that the Delay-Multiply-and-Sum (DMAS) algorithm achieved the highest signal-to-clutter ratios (SCRs) for the five clinical case studies, but did not consider the potential impact of variations in breast dielectric properties between the five patients [22]. However, it is known that an incorrect estimate of the breast dielectric properties can impair the image quality of radar-based breast images [23]. In particular, assuming the same estimate of breast dielectric properties for each test case has been shown to impair the sensitivity of radar-based breast imaging where tumors are not correctly detected [24].…”