SPECTROSCOPIC ADMITTIVITY IMAGING OF BIOLOGICAL TISSUES

IF 0.3 Q4 MATHEMATICS, APPLIED
Tingting Zhang, T. Bera, E. Woo, J. Seo
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引用次数: 2

Abstract

Medical imaging techniques have evolved to expand our ability to visualize new contrast information of electrical, optical, and mechanical properties of tissues in the human body using noninvasive measurement methods. In particular, electrical tissue property imaging techniques have received considerable attention for the last few decades since electrical properties of biological tissues and organs change with their physiological functions and pathological states. We can express the electrical tissue properties as the frequency-dependent admittivity, which can be measured in a macroscopic scale by assessing the relation between the timeharmonic electric field and current density. The main issue is to reconstruct spectroscopic admittivity images from 10 Hz to 1 MHz, for example, with reasonably high spatial and temporal resolutions. It requires a solution of a nonlinear inverse problem involving Maxwell’s equations. To solve the inverse problem with practical significance, we need deep knowledge on its mathematical formulation of underlying physical phenomena, implementation of image reconstruction algorithms, and practical limitations associated with the measurement sensitivity, specificity, noise, and data acquisition time. This paper discusses a number of issues in electrical tissue property imaging modalities and their future directions.
生物组织的光谱导纳成像
医学成像技术的发展扩大了我们使用无创测量方法可视化人体组织的电学、光学和机械特性的新对比信息的能力。特别是,由于生物组织和器官的电特性随其生理功能和病理状态而变化,电组织特性成像技术在过去几十年中受到了相当大的关注。我们可以将电组织特性表示为频率相关导纳,可以通过评估时谐电场与电流密度之间的关系在宏观尺度上测量。主要问题是重建光谱导纳图像从10hz到1mhz,例如,具有相当高的空间和时间分辨率。它需要一个涉及麦克斯韦方程组的非线性逆问题的解。为了解决具有实际意义的逆问题,我们需要深入了解其底层物理现象的数学公式,图像重建算法的实现以及与测量灵敏度,特异性,噪声和数据采集时间相关的实际限制。本文讨论了电组织特性成像模式中的一些问题及其未来发展方向。
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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