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arXiv 1809.07060math.APmath.OC
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如何在热声层析成像中定位传感器?

How locating sensors in thermo-acoustic tomography?

Maïtine Bergounioux, Elie Bretin, Yannick Privat

摘要:

热声断层扫描是一种非侵入性的医学成像技术,构成了一个精确和廉价的替代X成像。其原理是用脉冲激励身体进行重建,引起不均匀的加热,从而使组织膨胀。这产生了用传感器测量的声波压力。然后可以通过求解逆问题来执行身体内部的非均匀性的重建,已知身体外部的声波的测量。由于所测量的压力的强度预期是小的,因此具有挑战性的问题在于以适当的方式定位传感器。本文致力于确定一个最佳的传感器位置,以实现这种重建。我们首先介绍了一个模型,涉及一个最小二乘功能站的第一系列的测量传感器的压力的观察,和一个可观测性的常数功能描述的质量重建。然后,我们确定一个合适的位置的传感器的两个系列的措施,在两个步骤:首先,我们重建可能的初始数据,通过解决最坏情况下的设计问题。其次,我们确定从这些初始条件的知识的最佳位置的传感器以最佳的方式观察相应的解的波动方程。远不是提供一个固有的解决方案定位传感器的一般问题,解决这个问题允许确定一个新的传感器位置,提高重建的质量之前,得到一系列新的措施。我们对这个模型进行了数学分析:特别是我们研究了存在性问题,并引入了一个数值算法来解决它。最后,一些数值2D模拟说明了我们的方法。

英文摘要:

Thermo-acoustic tomography is a non-invasive medical imaging technique, constituting a precise and cheap alternative to X-imaging. The principle is to excite a body to reconstruct with a pulse inducing an inhomogeneous heating and therefore expansion of tissues. This creates an acoustic wave pressure which is measured with sensors. The reconstruction of heterogeneities inside the body can be then performed by solving an inverse problem, knowing measurements of the acoustic waves outside the body. As the intensity of the measured pressure is expected to be small, a challenging problem consists in locating the sensors in a adequate way. This paper is devoted to the determination of an optimal sensors location to achieve this reconstruction. We first introduce a model involving a least square functional standing for an observation of the pressure for a first series of measures by sensors, and an observability-like constant functional describing for the quality of reconstruction. Then, we determine an appropriate location of sensors for two series of measures, in two steps: first, we reconstruct possible initial data by solving a worst-case design like problem. Second, we determine from the knowledge of these initial conditions the optimal location of sensors for observing in the best way the corresponding solution of the wave equation. Far from providing an intrinsic solution to the general issue of locating sensors, solving this problem allows to determine a new sensors location improving the quality of reconstruction before getting a new series of measures. We perform a mathematical analysis of this model: in particular we investigate existence issues and introduce a numerical algorithm to solve it. Eventually, several numerical 2D simulations illustrate our approach.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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