Grant: Idea to Innovation

Compressive Sampling (CS) is a revolutionary technique based on the premise that certain types of signals can be reconstructed from far fewer measurements than are required by the classic sampling theories. Medical imaging in particular can benefit significantly from CS due to the associated reduction in image acquisition time, which is important to minimize radiation dose in techniques like CT, and motion artifacts in techniques like MRI. Fourier Domain Optical Coherence Tomography (FD OCT) is a fairly well established technology for ophthalmic imaging. Techniques that reduce motion artifacts have recently been implemented to mitigate the issue of subject eye motion during OCT imaging. However, these techniques involve motion tracking, which requires costly hardware, and cannot be retrofitted to the large number of FD OCT systems already in the field. In this I2I application we propose CS as a low-cost alternative to motion tracking for FD OCT, in particular for retrofitting the existing installed base of systems, and for next generation systems where hardware-based motion tracking is not feasible because of cost or other factors. Recently, we reported a proof of concept demonstration of CS to reduce the scan time, increase image resolution, and improve de-noising results. Our current goal is to develop the CS-based technology toward use in a clinical environment, thereby improving its marketability. We will investigate rapid volumetric acquisition for CS OCT, perform a validation study of the technology on clinical data, and establish a real time CS reconstruction solution based on massively parallel computing architectures (graphics processing units). The second focus of this application is to generate novel technology for data compression, which further expands the marketability of this invention to OCT data reading centres, which could benefit from reduced volumes of data.