Medical image processing using brain emulation

A high performance implementation of an algorithm based on the learning process of the human vision as an edge-enhancing filter for medical images is proposed. It is based on a cognitive image processing algorithm that emulates the contour identification process that is believed to be used by the human brain. The algorithm is implemented on an innovative and high performance embedded system for real-time pattern matching. The system design uses Field Programmable Gate Arrays (FPGAs) and the powerful Associative Memory chip (an ASIC) to achieve real-time performance. We present the first results of the algorithm as a 3-D edge detection filter using Magnetic Resonance Images (MRI).