Terahertz biomedical imaging: From multivariate analysis and detection to material parameter extraction

A. Al-Ibadi, J. Sleiman, Q. Cassar, G. MacGrogan, H. Balacey, T. Zimmer, P. Mounaix, Jean-Paul Guillet
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引用次数: 2

Abstract

Terahertz imaging is an interesting route for biomedical analysis. In particular, cancer imaging is a subject of study for different teams [1,2]. A work is done in Bordeaux in partnership with a hospital to do terahertz analysis of breast tissue. This work is done in reflection with time domain imaging setup with fresh samples. The aim is to accurately assess tumor margins and which could in the future allow a quick validation of the precision of the surgical procedure and know if new surgery should be performed. We have presented in a previous paper [3] the use of automatic methods of image generation with different parameters [4] in order to explore the different contrasts that exist in the time and frequency domain data of a terahertz imaging system. These methods make it possible to locate and identify areas containing breast tissue, cancer or fat. In this communication, we propose to present new results and images with both multivariate approaches (like multivariate component analysis) and material parameter extraction to give both 2D localization and comprehensive parameter description.
太赫兹生物医学成像:从多变量分析和检测到材料参数提取
太赫兹成像是生物医学分析的一个有趣途径。特别是,癌症成像是不同团队的研究课题[1,2]。一项工作是在波尔多与一家医院合作对乳房组织进行太赫兹分析。这项工作是在反射与时域成像设置与新鲜样品。目的是准确地评估肿瘤边缘,这可以在未来快速验证手术的准确性,并知道是否应该进行新的手术。我们在之前的论文[3]中提出了使用不同参数的自动图像生成方法[4],以探索太赫兹成像系统的时间和频域数据中存在的不同反差。这些方法使定位和识别含有乳腺组织、癌症或脂肪的区域成为可能。在这篇文章中,我们建议使用多元方法(如多元成分分析)和材料参数提取来呈现新的结果和图像,以提供二维定位和全面的参数描述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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