There has been great interest in recent times in the use of elastography for the characterization of human tissue. Digital Image Elasto-Tomography is a novel breast cancer pre-screening technique under development at the University of Canterbury, which aims to identify and locate stiff areas within the breast that require further investigation using images of the surface motion alone. A calibrated array of five digital cameras is used to capture surface motion of the breast under harmonic actuation. The forward problem, that is the resulting motion for a given mechanical property distribution, is calculated using the Finite Element Method. The inverse problem is to find the mechanical properties which reproduce the measured surface motion through numerical simulation. A reconstruction algorithm is developed using a shape based description to reduce the number of parameters in the inverse problem. A parallel Genetic Algorithm is developed for parameter optimization. A geometric method termed Fitness Function Analysis is shown to improve the inclusion location optimization problem. The ensemble of solutions generated using the Genetic Algorithm is used to produce an optimal and a credible region for inclusion location. Successful single frequency phantom reconstructions are presented. An effective way of combining information from multi-frequency phantom data by examining the characteristics of the measured surface motion using data quality metrics is developed and used to produce improved reconstructions. Results from numerical simulation datasets and a two inclusion phantom used to test the optimization of multiple and ellipsoidal inclusions indicate that although two inclusions can be successfully reconstructed, the single inclusions assumption may suffice even in irregular, heterogeneous cases. This assumption was used to successfully locate the stiffest inclusion in a phantom containing multiple inclusions of differing stiffness based on three multi-frequency datasets. The methods developed in phantoms are applied to three in vivo cases for both single and multi-frequency data with limited success. This thesis builds on previous work undertaken at the University of Canterbury. The original contributions in this work are as follows. A new reconstruction algorithm combining a genetic algorithm with fitness function analysis is developed. The most realistic tissue mimicking phantoms to date are used. An ellipsoidal shape-based description is presented, and applied to the first multi-inclusion reconstructions in DIET. This work presents the first reconstruction using meshes created directly from data using a meshing algorithm developed by Jonas Biehler. A multi-frequency cost function is developed to produce the first multi-frequency and in vivo reconstructions using DIET data.

Breast cancer is a major health problem across the globe. Many incidences in the underdeveloped nations go unreported, due to non-availability or lack of access to breast screening programs. Mammography, the current gold standard for breast screening, comes with several inherent limitations in terms of cost, radiation exposure, and associated discomfort. The cost of equipment and personnel alone puts mammography out of reach for most developing nations. Hence, there is a great and growing need for an adjunct breast screening modality, within reach of general masses, especially in the overpopulated, underdeveloped countries. Digital Image Elasto Tomography (DIET) is intended to be a low cost, radiation free, noninvasive and portable breast cancer screening modality that will be accessible to the general population and will encourage more women to undergo breast screening. The DIET imaging concept induces mechanical vibrations into a breast and its surface motion is captured with digital cameras and reconstructed in 3D, for elastic characterization of the breast tissues. Ex-vivo trials and limited in-vivo trials show promise in breast cancer diagnostic evaluation. The current DIET system is, as noted, functional, but not suitable for wide scale screening. There are significant development issues in hardware, software and algorithms required to improve its speed of testing and quality of diagnostic results. The main aim of this thesis is to overcome these issues taking the DIET system from the lab to a more directly useful and usable system. This thesis presents a complete design development and analysis of the DIET clinical system, developing a prototype suitable for large-scale in-vivo trials, to establish the sensitivity and specificity of this novel technology. The major components of this research are development, of the imaging array to capture surface motion, strobe illumination for reliable image capture, actuation system to vibrate the breast harmonically, remote positioning of the actuator, ergonomic design of the imaging device, and the development of a graphical interface for easy operation of the system. Moreover, anthropomorphic silicone breast phantoms suitable for diagnostic evaluation of elastographic imaging modalities, including DIET and MRE are also presented. A new approach in software based DIET diagnosis through separate modal analysis, focusing on the second natural frequency of the breast, is also presented. Finally, the new DIET technology developed is validated ex-vivo, using two different diagnostic techniques. The trials results are positive and demonstrate viability of this new technology for commercialization. All of these aspects have advanced the clinical and technological future of this overall DIET system concept. The overall thesis makes several technical advances necessary to advance the DIET concept from a purely research concept to clinical feasibility. These advances are coupled within an advanced design to create an all new clinical prototype system. The final, validated result shows the clinical potential, both ex-vivo and in-vivo, and clinical feasibility of the DIET concept and this research.