Andrew Tizzard

Bio: Andrew Tizzard is an academic researcher from Middlesex University. The author has contributed to research in topics: Electrical impedance tomography & Finite element method. The author has an hindex of 12, co-authored 41 publications receiving 1184 citations.

GREIT: a unified approach to 2D linear EIT reconstruction of lung images.

Abstract: Electrical impedance tomography (EIT) is an attractive method for clinically monitoring patients during mechanical ventilation, because it can provide a non-invasive continuous image of pulmonary impedance which indicates the distribution of ventilation. However, most clinical and physiological research in lung EIT is done using older and proprietary algorithms; this is an obstacle to interpretation of EIT images because the reconstructed images are not well characterized. To address this issue, we develop a consensus linear reconstruction algorithm for lung EIT, called GREIT (Graz consensus Reconstruction algorithm for EIT). This paper describes the unified approach to linear image reconstruction developed for GREIT. The framework for the linear reconstruction algorithm consists of (1) detailed finite element models of a representative adult and neonatal thorax, (2) consensus on the performance figures of merit for EIT image reconstruction and (3) a systematic approach to optimize a linear reconstruction matrix to desired performance measures. Consensus figures of merit, in order of importance, are (a) uniform amplitude response, (b) small and uniform position error, (c) small ringing artefacts, (d) uniform resolution, (e) limited shape deformation and (f) high resolution. Such figures of merit must be attained while maintaining small noise amplification and small sensitivity to electrode and boundary movement. This approach represents the consensus of a large and representative group of experts in EIT algorithm design and clinical applications for pulmonary monitoring. All software and data to implement and test the algorithm have been made available under an open source license which allows free research and commercial use.

Depth sensitivity and image reconstruction analysis of dense imaging arrays for mapping brain function with diffuse optical tomography

Abstract: The development of diffuse optical tomography (DOT) instrumentation for neuroimaging of humans is challenging due to the large size and the geometry of the head and the desire to distinguish signals at different depths. One approach to this problem is to use dense imaging arrays that incorporate measurements at different source-detector distances. We previously developed a high-density DOT system that is able to obtain retinotopic measurements in agreement with functional magnetic resonance imaging and positron emission tomography. Further extension of high-density DOT neuroimaging necessitates a thorough study of the measurement and imaging sensitivity that incorporates the complex geometry of the head--including the head curvature and layered tissue structure. We present numerical simulations using a finite element model of the adult head to study the sensitivity of the measured signal as a function of the imaging array and data sampling strategy. Specifically, we quantify the imaging sensitivity available within the brain (including depths beyond superficial cortical gyri) as a function of increasing the maximum source-detector separation included in the data. Through the use of depth related sensitivity analysis, it is shown that for a rectangular grid [with 1.3 cm first nearest neighbor (NN) spacing], second NN measurements are sufficient to record absorption changes along the surface of the brain's cortical gyri (brain tissue depth 15 mm).

Generating accurate finite element meshes for the forward model of the human head in EIT.

Abstract: The use of realistic anatomy in the model used for image reconstruction in EIT of brain function appears to confer significant improvements compared to geometric shapes such as a sphere. Accurate model geometry may be achieved by numerical models based on magnetic resonance images (MRIs) of the head, and this group has elected to use finite element meshing (FEM) as it enables detailed internal anatomy to be modelled and has the capability to incorporate information about tissue anisotropy. In this paper a method for generating accurate FEMs of the human head is presented where MRI images are manually segmented using custom adaptation of industry standard commercial design software packages. This is illustrated with example surface models and meshes from adult epilepsy patients, a neonatal baby and a phantom latex tank incorporating a real skull. Mesh quality is assessed in terms of element stretch and hence distortion.

Bioimpedance imaging: an overview of potential clinical applications.

Abstract: Electrical Impedance Tomography (EIT) is an imaging technique based on multiple bio impedance measurements to produce a map (image) of impedance or changes in impedance across a region. Its origins lay in geophysics where it is still used to today. This review highlights potential clinical applications of EIT. Beginning with a brief overview of the underlying principles behind the modality, it describes the background research leading towards the development of the application of EIT for monitoring pulmonary function, detecting and localising tumours and monitoring brain function.

Recent advances in diffuse optical imaging.

Abstract: We review the current state-of-the-art of diffuse optical imaging, which is an emerging technique for functional imaging of biological tissue. It involves generating images using measurements of visible or near-infrared light scattered across large (greater than several centimetres) thicknesses of tissue. We discuss recent advances in experimental methods and instrumentation, and examine new theoretical techniques applied to modelling and image reconstruction. We review recent work on in vivo applications including imaging the breast and brain, and examine future challenges.

Diffuse optics for tissue monitoring and tomography

Abstract: This review describes the diffusion model for light transport in tissues and the medical applications of diffuse light. Diffuse optics is particularly useful for measurement of tissue hemodynamics, wherein quantitative assessment of oxy- and deoxy-hemoglobin concentrations and blood flow are desired. The theoretical basis for near-infrared or diffuse optical spectroscopy is developed, and the basic elements of diffuse optical tomography are outlined. We also discuss diffuse correlation spectroscopy, a technique whereby temporal correlation functions of diffusing light are transported through tissue and are used to measure blood flow. Essential instrumentation is described, and representative brain and breast functional imaging and monitoring results illustrate the workings of these new tissue diagnostics.

Numerical methods for engineers

Abstract: The fifth edition of "Numerical Methods for Engineers" continues its tradition of excellence. Instructors love this text because it is a comprehensive text that is easy to teach from. Students love it because it is written for them--with great pedagogy and clear explanations and examples throughout. The text features a broad array of applications, including all engineering disciplines. The revision retains the successful pedagogy of the prior editions. Chapra and Canale's unique approach opens each part of the text with sections called Motivation, Mathematical Background, and Orientation, preparing the student for what is to come in a motivating and engaging manner. Each part closes with an Epilogue containing sections called Trade-Offs, Important Relationships and Formulas, and Advanced Methods and Additional References. Much more than a summary, the Epilogue deepens understanding of what has been learned and provides a peek into more advanced methods. Approximately 80% of the end-of-chapter problems are revised or new to this edition. The expanded breadth of engineering disciplines covered is especially evident in the problems, which now cover such areas as biotechnology and biomedical engineering. Users will find use of software packages, specifically MATLAB and Excel with VBA. This includes material on developing MATLAB m-files and VBA macros.