Parameter selection in limited data cone-beam CT reconstruction using edge preserving total variation algorithms

There are a number of powerful total variation (TV) regularization methods with
 great promises in limited data cone-beam CT reconstruction with an enhancement
 of image quality. These promising TV methods require careful selection of image
 reconstruction parameters for which there is no well established criteria. This pa-
 per presents a comprehensive valuation of parameter selection in a number of major
 TV-based reconstruction algorithms. The appropriate way of selecting the values for
 each individual parameter has been suggested. Finally, the new adaptive-weighted
 projection-controlled steepest descent (AwPCSD) algorithm is presented which imple-
 ments the edge-preserving function for CBCT reconstruction with limited data. The
 proposed algorithm shows signicant robustness compared to other three existing al-
 gorithms: ASD-POCS, AwASD-POCS and PCSD. The proposed AwPCSD algorithm
 is able to preserve the edges of the reconstructed images better with less sensitive pa-
 rameters to tune

Tracking boundary movement and exterior shape modelling in lung EIT imaging

Electrical impedance tomography (EIT) has shown significant promise for lung imaging. One key challenge for EIT in this application is the movement of electrodes during breathing, which introduces artefacts in reconstructed images. Various approaches have been proposed to compensate for electrode movement, but no comparison of these approaches is available. This paper analyses boundary model mismatch and electrode movement in lung EIT. The aim is to evaluate the extent to which various algorithms tolerate movement, and to determine if a patient specific model is required for EIT lung imaging. Movement data are simulated from a CT-based model, and image analysis is performed using quantitative figures of merit. The electrode movement is modelled based on expected values of chest movement and an extended Jacobian method is proposed to make use of exterior boundary tracking. Results show that a dynamical boundary tracking is the most robust method against any movement, but is computationally more expensive. Simultaneous electrode movement and conductivity reconstruction algorithms show increased robustness compared to only conductivity reconstruction. The results of this comparative study can help develop a better understanding of the impact of shape model mismatch and electrode movement in lung EIT