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The emerging need for the current medical devices to achieve immediate visualization and performing diagnostic imaging at real time augurs the demand for high computational power of the associated electronic circuitry. The demand for such a high computational requirement is often met by using software methods to accelerate the computation, which is possible only to a certain extent, impairing the feasibility of real-time imaging and diagnosis. In this paper, a new method of using digital signal processors (DSPs) with a specialized pipelined vision processor (PVP) embedded at the hardware level to accelerate the routinely time-consuming imaging computation is proposed and validated. A lab prototype is built for the feasibility study and clinical validation of the proposed technique. This unique architecture of the PVP in a dual-core DSP offers a high-performance accelerated framework along with its large on-chip memory resources, and reduced bandwidth requirement provides as an ideal architecture for reliable medical computational needs. We have taken two sets sample studies from SPECT for validation-27 cases of thyroid medical history and 20 cases of glomerular filtration rate of kidneys. The results were compared with definitive post-scan SIEMENS image analysis software. From the statistical results, it is clearly shown that this method achieved very superior accuracy and 250% acceleration of computational speed.

A Practical Design and Implementation of a Low-Cost Platform for Real-Time Diagnostic Imaging