Level-set-based reconstruction algorithm for EIT lung images: first clinical results.
@article{Rahmati2012LevelsetbasedRA,
title={Level-set-based reconstruction algorithm for EIT lung images: first clinical results.},
author={Peyman Rahmati and Manuchehr Soleimani and Sven Pulletz and In{\'e}z Frerichs and Andy Adler},
journal={Physiological measurement},
year={2012},
volume={33 5},
pages={
739-50
}
}We show the first clinical results using the level-set-based reconstruction algorithm for electrical impedance tomography (EIT) data. The level-set-based reconstruction method (LSRM) allows the reconstruction of non-smooth interfaces between image regions, which are typically smoothed by traditional voxel-based reconstruction methods (VBRMs). We develop a time difference formulation of the LSRM for 2D images. The proposed reconstruction method is applied to reconstruct clinical EIT data of a…
27 Citations
Functional Validation and Comparison Framework for EIT Lung Imaging
- MedicinePloS one
- 2014
Backprojection works surprisingly well, supporting the validity of previous studies in lung EIT and indicating 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.
Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method
- PhysicsScientific reports
- 2016
Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution, and the DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs.
A Parametric Level Set Method for Electrical Impedance Tomography
- EngineeringIEEE Transactions on Medical Imaging
- 2018
Experimental and simulation results show that PLS method has significant improvement in image quality compared with the TLS reconstruction, and is among the first ones using experimental EIT data.
A shape-based quality evaluation and reconstruction method for electrical impedance tomography.
- MathematicsPhysiological measurement
- 2015
A two-sided extension of this concept by first introducing a novel method of evaluation and a linear method of reconstruction that uses orthonormal eigenimages as training data and a tunable desired point spread function are proposed.
Data preprocessing methods for electrical impedance tomography: a review.
- MathematicsPhysiological measurement
- 2020
The results show that all the reviewed methods can enhance the quality of EIT reconstructed images to different extents, and there is an optimal one under any given reconstruction algorithm.
A GREIT-type linear reconstruction algorithm for EIT using eigenimages
- Mathematics
- 2013
By using different sets of training data, the creation of an individually optimized linear method of reconstruction is possible and the general feasibility of using eigenimages is demonstrated and compared to the standard approach.
An experimental clinical evaluation of EIT imaging with ℓ1 data and image norms.
- MathematicsPhysiological measurement
- 2013
The results showed that an ℓ1 solution is not only more robust to unavoidable measurement errors in a clinical setting, but it also provides high contrast resolution on organ boundaries.
A level set based regularization framework for EIT image reconstruction
- Mathematics
- 2013
Electrical Impedance Tomography (EIT) reconstructs the conductivity distribution within a medium from electrical stimulation and measurements at the medium surface. Level set based reconstruction…
Multi-phase flow monitoring with electrical impedance tomography using level set based method
- Mathematics
- 2015
A hybrid regularization algorithm for high contrast tomographic image reconstruction
- MathematicsICIP 2013
- 2013
The common Level set based reconstruction method (LSRM) is applied to solve a piecewise constant inverse problem using one level set function and considers two different conductivity quantities for…
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