Recent work to redesign the EIDORS software structure in order to simplify its use and provide a uniform interface, permitting easier modification and customization is described.
This paper describes the unified approach to linear image reconstruction developed for GREIT (Graz consensus Reconstruction algorithm for EIT), which represents the consensus of a large and representative group of experts in EIT algorithm design and clinical applications for pulmonary monitoring.
A maximum a posteriori (MAP) approach to linearized image reconstruction using knowledge of the noise variance of the measurements and the covariance of the conductivity distribution has the advantage of an intuitive interpretation of the algorithm parameters as well as fast image reconstruction.
A new classification of core processes involved in chest EIT examinations and data analysis is provided, and a structured framework to categorise and understand the relationships among analysis approaches and their clinical roles is provided.
Electrical impedance tomography image reconstruction algorithms with regularization based on the total variation (TV) functional are suitable for in vivo imaging of physiological data and shows improved ability to reconstruct sharp contrasts compared to traditional quadratic regularization.
A potential vulnerability in biometric encryption systems that allows a less-than-brute force regeneration of the secret and an estimate of the enrolled image is described.
Data show that Penh is problematic in the sense that it is strain specific; it behaves very differently in BALB/c and C57BL/6 mice, and it is inappropriate to use UP parameters in general, and Penh specifically, as substitute variables for invasive mechanical indexes such as Rl.
This review paper focuses on describing the image interpretation “pathway” of EIT-based measures, and reviews this pathway, from Tissue Electrical Properties, EIT Electrodes & Hardware, Sensitivity, Image Reconstruction, Image Processing to EIT Measures.
It is argued that lung EIT research has arrived at an important transition, and it is now clear that valid and reproducible physiological information is available from EIT lung images, and possible clinical scenarios in which EIT could play an important role are developed.
Results show that the traditional (and still most common) adjacent stimulation and measurement patterns have by far the poorest performance, and are presented as a call to action: adjacent patterns are harmful, and should be abandoned.