A Hybrid Segmentation and D-Bar Method for Electrical Impedance Tomography

نویسندگان

  • S. J. Hamilton
  • Juan Manuel Reyes
  • Samuli Siltanen
  • X. Zhang
چکیده

The regularized D-bar method for electrical impedance tomography (EIT) provides a rigorous mathematical approach for solving the full nonlinear inverse problem directly, i.e., without iterations. It is based on a low-pass filtering in the (nonlinear) frequency domain. However, the resulting D-bar reconstructions are inherently smoothed, leading to a loss of edge distinction. In this paper, a novel method that combines a D-bar approach with the edge-preserving nature of total variation (TV) regularization is presented. The method also includes a data-driven contrast adjustment technique guided by the key functions (CGO solutions) of the D-bar method. The new TV-enhanced D-bar method produces reconstructions with sharper edges and improved contrast. This is achieved by using the TV-induced edges to increase the truncation radius of the scattering data in the nonlinear frequency domain, thereby increasing the radius of the low-pass filter. The algorithm is tested on numerically simulated noisy EIT data and demonstrates significant improvements in edge preservation and contrast which can be highly valuable for absolute EIT imaging.

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عنوان ژورنال:
  • SIAM J. Imaging Sciences

دوره 9  شماره 

صفحات  -

تاریخ انتشار 2016