Comparison of total variation algorithms for electrical impedance tomography.

The applications of total variation (TV) algorithms for electrical impedance tomography (EIT) have been investigated. The use of the TV regularisation technique helps to preserve discontinuities in reconstruction, such as the boundaries of perturbations and sharp changes in conductivity, which are unintentionally smoothed by traditional l2 norm regularisation. However, the non-differentiability of TV regularisation has led to the use of different algorithms. Recent advances in TV algorithms such as the primal dual interior point method (PDIPM), the linearised alternating direction method of multipliers (LADMM) and the spilt Bregman (SB) method have all been demonstrated successful EIT applications, but no direct comparison of the techniques has been made. Their noise performance, spatial resolution and convergence rate applied to time difference EIT were studied in simulations on 2D cylindrical meshes with different noise levels, 2D cylindrical tank and 3D anatomically head-shaped phantoms containing vegetable material with complex conductivity. LADMM had the fastest calculation speed but worst resolution due to the exclusion of the second-derivative; PDIPM reconstructed the sharpest change in conductivity but with lower contrast than SB; SB had a faster convergence rate than PDIPM and the lowest image errors.

A Reconstruction-Classification Method for Multifrequency Electrical Impedance Tomography.

Multifrequency Electrical Impedance Tomography is an imaging technique which distinguishes biological tissues by their unique conductivity spectrum. Recent results suggest that the use of spectral constraints can significantly improve image quality. We present a combined reconstruction-classification method for estimating the spectra of individual tissues, whilst simultaneously reconstructing the conductivity. The advantage of this method is that a priori knowledge of the spectra is not required to be exact in that the constraints are updated at each step of the reconstruction. In this paper, we investigate the robustness of the proposed method to errors in the initial guess of the tissue spectra, and look at the effect of introducing spatial smoothing. We formalize and validate a frequency-difference variant of reconstruction-classification, and compare the use of absolute and frequency-difference data in the case of a phantom experiment.

Interventional Photoacoustic Imaging of the Human Placenta with Ultrasonic Tracking for Minimally Invasive Fetal Surgeries.

Image guidance plays a central role in minimally invasive fetal surgery such as photocoagulation of inter-twin placental anastomosing vessels to treat twin-to-twin transfusion syndrome (TTTS). Fetoscopic guidance provides insufficient sensitivity for imaging the vasculature that lies beneath the fetal placental surface due to strong light scattering in biological tissues. Incomplete photocoagulation of anastamoses is associated with postoperative complications and higher perinatal mortality. In this study, we investigated the use of multi-spectral photoacoustic (PA) imaging for better visualization of the placental vasculature. Excitation light was delivered with an optical fiber with dimensions that are compatible with the working channel of a fetoscope. Imaging was performed on an ex vivo normal term human placenta collected at Caesarean section birth. The photoacoustically-generated ultrasound signals were received by an external clinical linear array ultrasound imaging probe. A vein under illumination on the fetal placenta surface was visualized with PA imaging, and good correspondence was obtained between the measured PA spectrum and the optical absorption spectrum of deoxygenated blood. The delivery fiber had an attached fiber optic ultrasound sensor positioned directly adjacent to it, so that its spatial position could be tracked by receiving transmissions from the ultrasound imaging probe. This study provides strong indications that PA imaging in combination with ultrasonic tracking could be useful for detecting the human placental vasculature during minimally invasive fetal surgery.

Multifrequency electrical impedance tomography using spectral constraints.

Multifrequency electrical impedance tomography (MFEIT) exploits the dependence of tissue impedance on frequency to recover an image of conductivity. MFEIT could provide emergency diagnosis of pathologies such as acute stroke, brain injury and breast cancer. We present a method for performing MFEIT using spectral constraints. Boundary voltage data is employed directly to reconstruct the volume fraction distribution of component tissues using a nonlinear method. Given that the reconstructed parameter is frequency independent, this approach allows for the simultaneous use of all multifrequency data, thus reducing the degrees of freedom of the reconstruction problem. Furthermore, this method allows for the use of frequency difference data in a nonlinear reconstruction algorithm. Results from empirical phantom measurements suggest that our fraction reconstruction method points to a new direction for the development of multifrequency EIT algorithms in the case that the spectral constraints are known, and may provide a unifying framework for static EIT imaging.