Level-set-based reconstruction algorithm for EIT lung images: first clinical results

Rahmati, Peyman; Soleimani, Masoud; Pulletz, Sven; Frerichs, Inéz; Adler, Andy

doi:10.1088/0967-3334/33/5/739

Cited by 30 publications

(22 citation statements)

References 31 publications

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“…To represent a two-dimensional closed interface, one can use the geometric nodes method [11] or the level sets method [14]. Here, we assume the deposit interface is smooth and star-shaped.…”

Section: (B) Permittivity and Interface Representationmentioning

confidence: 99%

Interface and permittivity simultaneous reconstruction in electrical capacitance tomography based on boundary and finite-elements coupling method

Ren

Dong

2016

Phil. Trans. R. Soc. A.

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Electrical capacitance tomography (ECT) is a non-destructive detection technique for imaging the permittivity distributions inside an observed domain from the capacitances measurements on its boundary. Owing to its advantages of non-contact, non-radiation, high speed and low cost, ECT is promising in the measurements of many industrial or biological processes. However, in the practical industrial or biological systems, a deposit is normally seen in the inner wall of its pipe or vessel. As the actual region of interest (ROI) of ECT is surrounded by the deposit layer, the capacitance measurements become weakly sensitive to the permittivity perturbation occurring at the ROI. When there is a major permittivity difference between the deposit and the ROI, this kind of shielding effect is significant, and the permittivity reconstruction becomes challenging. To deal with the issue, an interface and permittivity simultaneous reconstruction approach is proposed. Both the permittivity at the ROI and the geometry of the deposit layer are recovered using the block coordinate descent method. The boundary and finite-elements coupling method is employed to improve the computational efficiency. The performance of the proposed method is evaluated with the simulation tests. This article is part of the themed issue ‘Supersensing through industrial process tomography’.

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Section: (B) Permittivity and Interface Representationmentioning

confidence: 99%

Interface and permittivity simultaneous reconstruction in electrical capacitance tomography based on boundary and finite-elements coupling method

Ren

Dong

2016

Phil. Trans. R. Soc. A.

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“…Meantime, level set method has become powerful and versatile tool for image processing and computational physics (Vese and Chan, 2002;Fedkiw, 2001, 2003;Chung et al, 2005), also it has found applications in shape reconstruction and inverse scattering (Dorn et al, 2000;Dorn and Lesselier, 2006). More recently, applications of level set method to electrical tomography (ET) problems have been proposed (Ito et al, 2001;Soleimani et al, 2006a,b;Rahmati et al, 2012;Rahmati and Adler, 2013). In Ito et al (2001), using values of Neumann data as well as values of solution in a thin layer along the domain, level set method together with steepest descent method has been employed to solve the inverse conductivity problem.…”

Section: Introductionmentioning

confidence: 99%

Multi-phase flow monitoring with electrical impedance tomography using level set based method

Liu

Khambampati

Kim

et al. 2015

Nuclear Engineering and Design

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“…[35], or the D-Bar method (e.g. [36]) were not evaluated, as they have seen little evaluation for thoracic EIT data (but see [37], [38]. However, we make the data and software publicly available to allow extending the comparison to a wider range of present and future algorithms.…”

Section: Introductionmentioning

confidence: 99%

Functional Validation and Comparison Framework for EIT Lung Imaging

et al. 2014

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IntroductionElectrical impedance tomography (EIT) is an emerging clinical tool for monitoring ventilation distribution in mechanically ventilated patients, for which many image reconstruction algorithms have been suggested. We propose an experimental framework to assess such algorithms with respect to their ability to correctly represent well-defined physiological changes. We defined a set of clinically relevant ventilation conditions and induced them experimentally in 8 pigs by controlling three ventilator settings (tidal volume, positive end-expiratory pressure and the fraction of inspired oxygen). In this way, large and discrete shifts in global and regional lung air content were elicited.MethodsWe use the framework to compare twelve 2D EIT reconstruction algorithms, including backprojection (the original and still most frequently used algorithm), GREIT (a more recent consensus algorithm for lung imaging), truncated singular value decomposition (TSVD), several variants of the one-step Gauss-Newton approach and two iterative algorithms. We consider the effects of using a 3D finite element model, assuming non-uniform background conductivity, noise modeling, reconstructing for electrode movement, total variation (TV) reconstruction, robust error norms, smoothing priors, and using difference vs. normalized difference data.Results and ConclusionsOur results indicate that, while variation in appearance of images reconstructed from the same data is not negligible, clinically relevant parameters do not vary considerably among the advanced algorithms. Among the analysed algorithms, several advanced algorithms perform well, while some others are significantly worse. Given its vintage and ad-hoc formulation backprojection works surprisingly well, supporting the validity of previous studies in lung EIT.

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Level-set-based reconstruction algorithm for EIT lung images: first clinical results

Cited by 30 publications

References 31 publications

Interface and permittivity simultaneous reconstruction in electrical capacitance tomography based on boundary and finite-elements coupling method

Interface and permittivity simultaneous reconstruction in electrical capacitance tomography based on boundary and finite-elements coupling method

Multi-phase flow monitoring with electrical impedance tomography using level set based method

Functional Validation and Comparison Framework for EIT Lung Imaging

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