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基于微波雷达的乳房成像的参数搜索算法:作为适应度函数的焦点质量指标。

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

机构信息

Electrical and Electronic Engineering, National University of Ireland Galway, H91 TK33 Galway, Ireland.

McGill University, Montréal, QC, Canada H3A 0G4.

出版信息

Sensors (Basel). 2017 Dec 6;17(12):2823. doi: 10.3390/s17122823.

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.

摘要

不准确的平均介电特性估计会对基于微波雷达的乳房图像产生显著影响。尽管如此,最近的患者成像研究仍使用固定估计,尽管已知该估计值因人而异。参数搜索算法是一种从重建的微波图像本身中估计平均介电特性的有前途的技术,而无需额外的硬件。在这项工作中,从点扩散函数中确定了准确重建图像的质量。由于准确重建的微波图像的质量与聚焦的微观和摄影图像的质量相似,因此这项工作提出使用聚焦质量指标来估计平均介电特性。通过在三维体积图像上使用介电不均匀性体模来评估参数搜索的稳健性。基于平均介电特性的非常广泛的初始估计,本文展示了这些指标如何可以用作参数搜索算法中的合适适应度函数,以重建清晰和聚焦的微波雷达图像。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8ddd/5751619/b94f92791108/sensors-17-02823-g001.jpg

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