This new CAD for automated analysis of OCT images offers adequate sensitivity and specificity to distinguish normal OCT images from those showing potential neovascular age-related macular degeneration. These results will enable its clinical validation and a subsequent cost-effectiveness assessment to be made before recommendations are made for population-screening purposes.

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Abstract

This paper describes an Active Vision System whose design assumes a distinction between fast or reactive and slow or background processes. Fast processes need to operate in cycles with critical timeouts that may affect system stability. While slow processes, though necessary, do not compromise system stability if its execution is delayed. Based on this simple taxonomy, a control architecture has been proposed and a prototype implemented that is able to track people in real-time with a robotic head while trying to identify the target. In this system, the tracking module is considered as the reactive part of the system while person identification is considered a background task. This demonstrator has been developed using a new generation DSP (TMS320C80) as a specialized coprocessor to deal with fast processes, and a commercial robotic head with a dedicated DSP-based motor controller. These subsystems are hosted by a standard Pentium-Pro PC running Windows NT where slow processes are executed. The flexibility achieved in the design phase and the preliminary results obtained so far seem to validate the approach followed to integrate time-critical and slow tasks on a heterogeneous hardware platform.