A DIRECT D-BAR METHOD FOR PARTIAL BOUNDARY DATA ELECTRICAL IMPEDANCE TOMOGRAPHY WITH A PRIORI INFORMATION
A DIRECT D-BAR METHOD FOR PARTIAL BOUNDARY DATA ELECTRICAL IMPEDANCE TOMOGRAPHY WITH A PRIORI INFORMATION
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DOI：
10.3934/ipi.2017020
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发表时间：
2017-06-01
影响因子：
1.3
通讯作者：
Hauptmann, Andreas
中科院分区：
文献类型：
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作者：
Alsaker, Melody;Hamilton, Sarah Jane;Hauptmann, Andreas
电阻抗断层扫描（EIT）是一种非侵入性成像模式，它使用表面电气测量来确定身体的内部电导率。EIT问题的数学公式是一个非线性和严重不适定的反问题，直接D-酒吧的方法已被证明是有用的，在提供噪声鲁棒的电导率重建。D-bar方法的最新进展允许使用仅来自域的一部分（例如，可以仅使用在身体的可接近部分上收集的数据来对仰卧的患者进行成像）。然而，D杆重建遭受损失的尖锐边缘，由于非线性低通滤波的测量数据，这个问题变得特别明显的情况下，部分边界数据。将先验数据直接包括到D-bar解决方案方法中大大提高了空间分辨率，允许检测潜在的病理或缺陷，即使没有假设它们在先验中的存在。这项工作结合了部分数据D-bar与先验数据，允许噪声鲁棒的电导率重建，大大提高了空间分辨率。该方法被证明是有效的噪声模拟EIT测量数据模拟医疗和工业成像场景。
Electrical Impedance Tomography (EIT) is a non-invasive imaging modality that uses surface electrical measurements to determine the internal conductivity of a body. The mathematical formulation of the EIT problem is a nonlinear and severely ill-posed inverse problem for which direct D-bar methods have proved useful in providing noise-robust conductivity reconstructions. Recent advances in D-bar methods allow for conductivity reconstructions using EIT measurement data from only part of the domain (e.g., a patient lying on their back could be imaged using only data gathered on the accessible part of the body). However, D-bar reconstructions suffer from a loss of sharp edges due to a nonlinear low-pass filtering of the measured data, and this problem becomes especially marked in the case of partial boundary data. Including a priori data directly into the D-bar solution method greatly enhances the spatial resolution, allowing for detection of underlying pathologies or defects, even with no assumption of their presence in the prior. This work combines partial data D-bar with a priori data, allowing for noise-robust conductivity reconstructions with greatly improved spatial resolution. The method is demonstrated to be effective on noisy simulated EIT measurement data simulating both medical and industrial imaging scenarios.