Title
Shape Reconstruction Using Boolean Operations in Electrical Impedance Tomography
Abstract
In this work, we propose a new shape reconstruction framework rooted in the concept of Boolean operations for electrical impedance tomography (EIT). Within the framework, the evolution of inclusion shapes and topologies are simultaneously estimated through an explicit boundary description. For this, we use B-spline curves as basic shape primitives for shape reconstruction and topology optimization. The effectiveness of the proposed approach is demonstrated using simulated and experimentally-obtained data (testing EIT lung imaging). In the study, improved preservation of sharp features is observed when employing the proposed approach relative to the recently developed moving morphable components-based approach. In addition, robustness studies of the proposed approach considering background inhomogeneity and differing numbers of B-spline curve control points are performed. It is found that the proposed approach is tolerant to modeling errors caused by background inhomogeneity and is also quite robust to the selection of control points.
Year
DOI
Venue
2020
10.1109/TMI.2020.2983055
IEEE Transactions on Medical Imaging
Keywords
DocType
Volume
Algorithms,Electric Impedance,Image Processing, Computer-Assisted,Lung,Tomography,Tomography, X-Ray Computed
Journal
39
Issue
ISSN
Citations 
9
0278-0062
2
PageRank 
References 
Authors
0.37
0
5
Name
Order
Citations
PageRank
Dong Liu1125.34
Danping Gu242.10
Danny Smyl332.08
jiansong deng445838.59
Jiangfeng Du5116.45