Effective Exploitation of Prior Information in Electrical Impedance Tomography for Thermal Monitoring of Hyperthermia Treatments

Ferraioli, F.; Formisano, A.; Martone, R.

doi:10.1109/tmag.2009.2012740

Cited by 19 publications

(21 citation statements)

References 10 publications

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“…Where, Ψ is a const (taken as 0.01), ∆Φ is the projection error which is defined as the L-2 norm of the difference between the calculated data and the measured data. Hence the regularization parameter λ in the PEPR method is given by: (15) In formula (15), the regularization parameter λ varies in the range from 0.01/3 to 0.01/2. It includes two primary considerations: (1) Due to the ill-posed characteristic of the inverse problem, the regularization should not be reduced with iterations to a too small value.…”

Section: Pepr Methodsmentioning

confidence: 99%

“…Being a non-invasive, nonradiating, non-ionizing and inexpensive methodology, EIT has been extensively studied in clinical diagnosis [6], biomedical engineering [7] and biotechnology [8]. Attempts are also being made to develop a better medical-EIT system (Fig.-1) for different clinical investigations [9][10][11][12][13][14][15][16][17][18] and long time patient monitoring. The first impedance imaging system, the Impedance Camera, was constructed by Henderson and Webster to study pulmonary edema in 1978 [19].…”

Section: Introductionmentioning

confidence: 99%

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Improving Image Quality in Electrical Impedance Tomography (EIT) Using Projection Error Propagation-Based Regularization (PEPR) Technique: A Simulation Study

Bera

Biswas

Rajan

et al. 2011

Journal of Electrical Bioimpedance

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A Projection Error Propagation-based Regularization (PEPR) method is proposed and the reconstructed image quality is improved in Electrical Impedance Tomography (EIT). A projection error is produced due to the misfit of the calculated and measured data in the reconstruction process. The variation of the projection error is integrated with response matrix in each iterations and the reconstruction is carried out in EIDORS. The PEPR method is studied with the simulated boundary data for different inhomogeneity geometries. Simulated results demonstrate that the PEPR technique improves image reconstruction precision in EIDORS and hence it can be successfully implemented to increase the reconstruction accuracy in EIT.><p><a href="http://dx.doi.org/10.5617/jeb.158" target="_blank">doi:10.5617/jeb.158 </a><br />J Electr Bioimp, vol. 2, pp. 2-12, 2011</p>

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Section: Pepr Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improving Image Quality in Electrical Impedance Tomography (EIT) Using Projection Error Propagation-Based Regularization (PEPR) Technique: A Simulation Study

Bera

Biswas

Rajan

et al. 2011

Journal of Electrical Bioimpedance

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“…This technology attracts significant research interest for its unique capability of noninvasive detection, real-time monitoring, and other advantages in clinical diagnosis [1], [2].…”

Section: Introductionmentioning

confidence: 99%

Optimized Excitation Mode for Generalized Back Projection Algorithm in 3-D EIT

Wang

Zhang

et al. 2015

IEEE Trans. Magn.

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Biomedical electrical impedance tomography (EIT) seeks to image the interior conductivity spatial distribution within a 3-D object. In this paper, we propose a novel excitation mode of 3-D EIT for generalized back projection algorithm (GBPA). The new injection configuration is optimized by particle swarm optimization making the equipotential distribution monotonic, so that the projection matrix of GBPA would be computed more accurate and available. In addition, the GBPA reconstruction results in the optimized mode are compared with those in multisection simultaneous adjacent excitation mode assessed by several metrics in simulation experiments.Index Terms-Electrical impedance tomography (EIT), generalized back projection algorithm (GBPA), optimization problems, particle swarm optimization (PSO).

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“…EIT does have this potential due to its high speed, sensitivity to the conductivity change of tumor and normal tissue at various frequencies [9, 10], and its ability to monitor tissue temperature in real time [11, 12]. In both cardiac EIT and EIT for monitoring liver tumour RFA, there are opportunities to add an additional internal electrode close to the region of interest (ROI) to improve EIT sensitivity to internal tissues and particularly to the tissue within the ROI.…”

Section: Introductionmentioning

confidence: 99%

A Local Region of Interest Imaging Method for Electrical Impedance Tomography with Internal Electrodes

Kwon

McEwan

et al. 2013

Computational and Mathematical Methods in Medicine

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Electrical Impedance Tomography (EIT) is a very attractive functional imaging method despite the low sensitivity and resolution. The use of internal electrodes with the conventional reconstruction algorithms was not enough to enhance image resolution and accuracy in the region of interest (ROI). We propose a local ROI imaging method with internal electrodes developed from careful analysis of the sensitivity matrix that is designed to reduce the sensitivity of the voxels outside the local region and optimize the sensitivity of the voxel inside the local region. We perform numerical simulations and physical measurements to demonstrate the localized EIT imaging method. In preliminary results with multiple objects we show the benefits of using an internal electrode and the improved resolution due to the local ROI image reconstruction method. The sensitivity is further increased by allowing the surface electrodes to be unevenly spaced with a higher density of surface electrodes near the ROI. Also, we analyse how much the image quality is improved using several performance parameters for comparison. While these have not yet been studied in depth, it convincingly shows an improvement in local sensitivity in images obtained with an internal electrode in comparison to a standard reconstruction method.

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Effective Exploitation of Prior Information in Electrical Impedance Tomography for Thermal Monitoring of Hyperthermia Treatments

Cited by 19 publications

References 10 publications

Improving Image Quality in Electrical Impedance Tomography (EIT) Using Projection Error Propagation-Based Regularization (PEPR) Technique: A Simulation Study

Improving Image Quality in Electrical Impedance Tomography (EIT) Using Projection Error Propagation-Based Regularization (PEPR) Technique: A Simulation Study

Optimized Excitation Mode for Generalized Back Projection Algorithm in 3-D EIT

A Local Region of Interest Imaging Method for Electrical Impedance Tomography with Internal Electrodes

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