Specialised Image Capture Systems for a DIET Breast Cancer Screening System
Digital Image-based Elasto-Tomography (DIET) is an emerging technology for non-invasive breast cancer screening. This technology actuates breast tissue and measures the surface motion using digital imaging technology. The internal distribution of stiffness is then reconstructed using Boundary Element or Finite Element Methods (FEM or BEM). However, obtaining accurate imaging at high frequency and high resolution in terms of numbers of pixels is challenging if enough accuracy is to be obtained in the motion sensing to deliver a useful result. The overall focus of such mechatronic and digitally centred systems is on providing a low-cost, radiation dose-free and portable screening system capable of screening numerous patients per day – in direct contrast to current low throughput, non-portable and high cost x-ray and MRI based approaches. Thus, DIET technology relies on obtaining high resolution images of a breasts surface under high frequency actuation, typically in the range of 50-100Hz. Off-the-shelf digital cameras and imaging elements are unable to capture images directly at these speeds. A method is presented for obtaining the required high speed image capture at a resolution of 1280x1024 pixels and actuation frequency of 100Hz. The prototype apparatus presented uses two imaging sensors in combination with frame grabbers and a dSpace™ control system, to produce an automated image capture system. The system integrates a precision controlled strobe lighting system to selectively capture sinusoids at different points in the sinusoidal cycle of response. The final working system produced images that enabled effective 3D motion tracking of the surface of a silicon phantom actuated at 100Hz. The surface of the phantom was strobed at pre-selected phases from 0 to 360 degrees, and an image was captured for each phase. The times at which image capture occurred were calculated for a phase lag increment of 10 degrees resulting in an image effectively every 0.00028s for the actuator cycle of 0.01s. The comparison of the actual trigger times and pre-selected ideal trigger times gave a mean absolute error of 1.4%, thus demonstrating the accuracy of the final system. Final validation is performed using this system to track motion in a silicon gel phantom. The motion is tracked accurately using a novel Euclidean Invariant signature method. Both cameras delivered similar results with over 90% of points tracked to within 1-2%. This level of accuracy confirms the ability to effectively accurately reconstruct the stiffness as validated in other related studies.