Moll Jochen, Kelly Thomas N, Byrne Dallan, Sarafianou Mantalena, Krozer Viktor, Craddock Ian J
Department of Physics, Goethe University of Frankfurt, Max-von-Laue-Straße 1, 60438 Frankfurt am Main, Germany.
Centre of Communications and Research, University of Bristol, Bristol BS8 1UB, UK.
Int J Biomed Imaging. 2014;2014:943549. doi: 10.1155/2014/943549. Epub 2014 Nov 11.
Conventional radar-based image reconstruction techniques fail when they are applied to heterogeneous breast tissue, since the underlying in-breast relative permittivity is unknown or assumed to be constant. This results in a systematic error during the process of image formation. A recent trend in microwave biomedical imaging is to extract the relative permittivity from the object under test to improve the image reconstruction quality and thereby to enhance the diagnostic assessment. In this paper, we present a novel radar-based methodology for microwave breast cancer detection in heterogeneous breast tissue integrating a 3D map of relative permittivity as a priori information. This leads to a novel image reconstruction formulation where the delay-and-sum focusing takes place in time rather than range domain. Results are shown for a heterogeneous dense (class-4) and a scattered fibroglandular (class-2) numerical breast phantom using Bristol's 31-element array configuration.
传统的基于雷达的图像重建技术应用于异质性乳腺组织时会失效,因为乳腺内部的相对介电常数未知或被假定为恒定。这在图像形成过程中会导致系统误差。微波生物医学成像的一个最新趋势是从被测物体中提取相对介电常数,以提高图像重建质量,从而增强诊断评估。在本文中,我们提出了一种基于雷达的新颖方法,用于在异质性乳腺组织中进行微波乳腺癌检测,该方法将相对介电常数的三维图作为先验信息进行整合。这导致了一种新颖的图像重建公式,其中延迟求和聚焦是在时间域而非距离域中进行的。使用布里斯托尔的31元阵列配置,给出了异质性致密(4类)和散在性纤维腺性(2类)数字乳腺模型的结果。