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Biomedical subjects

G J Daniell

Publications and source records attributed to G J Daniell.

6 recordsLinked to original sources
PubMed2001

Adaptive mesh refinement techniques for electrical impedance tomography.

Adaptive mesh refinement techniques can be applied to increase the efficiency of electrical impedance tomography reconstruction algorithms by reducing computational and storage cost as well as providing problem-dependent solution structures. A self-adaptive refinement algorithm based on an a posteriori error estimate has been developed and its results are shown in comparison with uniform mesh refinement for a simple head model.

Algorithms↗
PubMed2000

High fidelity imaging and high performance computing in nonlinear EIT.

We show that nonlinear EIT provides images with well defined characteristics when smoothness of the image is used as a constraint in the reconstruction process. We use the gradient of the logarithm of resistivity as an effective measure of image smoothness, which has the advantage that resistivity and conductivity are treated with equal weight. We suggest that a measure of the fidelity of the image to the object requires the explicit definition and application of such a constraint. The algorithm is applied to the simulation of intra-ventricular haemorrhaging (IVH) in a simple head model. The results indicate that a 5% increase in the blood content of the ventricles would be easily detectable with the noise performance of contemporary instrumentation. The possible implementation of the algorithm in real time via high performance computing is discussed.

Algorithms↗
PubMed1998

Nonlinear reconstruction constrained by image properties in electrical impedance tomography.

It is proposed that image quality, for example the degree of roughness, in electrical impedance tomography is the essential measure required to regularize nonlinear reconstruction. Most previously published work has addressed efficiency, stabilization and speed of reconstruction and has overlooked the targeted image qualities. The measure of quality adopted is the mean square gradient of the logarithm of resistivity which, in combination with the chi2 statistic as a measure of the fit to the data, is minimized by iteration until convergence to a stable image is achieved. This penalty function is invariant to the scale of the resistivity and to the interchange of resistivity and conductivity. The algorithm is tested on computer simulated data and on measurements from a cylindrical tank of electrolyte. The results demonstrate the increased image definition that it would be possible to achieve as data acquisition systems are improved. The images show how a reduction in resolution can be traded for reduced noise artefacts, by selecting an appropriate target chi2.

Algorithms↗
PubMed1998

Electrical impedance tomography with compensation for electrode positioning variations.

Ideally electrical impedance tomography (EIT) should not be oversensitive to electrode positions, but this conflicts with efforts to produce high-resolution images. Two procedures are presented that balance reducing the sensitivity to electrode position errors with generating practicable EIT images. The first provides a criterion based on electrode sensitivity for regularizing the reconstruction through spectral expansion. The main consequences of this are that smoother images are produced and the number of artefacts and their magnitude are generally reduced. The second modification uses the recorded data to compensate for electrode movements that have occurred after the reference data were measured. Image smoothness is used as the criterion for the readjustment. Computer simulation tests have shown that this modification produces improved image fidelity.

Biophysical Phenomena↗
PubMed1995

Deconvolution of planar scintigrams by maximum entropy.

Planar scintigrams are deconvolved with a point spread function using the maximum entropy method with the aim of improving image quality. The technique requires the specification of several parameters. These are related to the level of noise present in the data and our a priori knowledge of the object imaged. The performance of the technique is tested for a wide range of these parameters using images of a Williams phantom in scattering material and a figure of merit, derived from the detectability of the smallest cold spot, is calculated. For close to optimal values of the parameters a factor of two improvement in the figure is found. A processed bone image shows improved contrast and resolution. Maximum entropy processing could be used to increase image quality or allow comparable image quality with reduced imaging time or patient dose.

Bone and Bones↗