Abstract
The availability of embedded processing platform has made it possible for many applications to utilize such platforms to go down in size and cost while maintaining the performance. In this work, we investigate the use of an embedded platform based on the OMAP processor for a challenging image reconstruction in magnetic resonance imaging. An algorithm based on the compressed sensing theory was implemented on the embedded platform and the performance was measured and compared to other platforms. This work shows interesting preliminary results and points to several future directions for performance optimization in utilizing such embedded platforms in practical medical imaging applications.