Options for new real-time image-processing architectures in CardioVascular systems

Low-dose X-ray imaging, diagnosis by image analysis and multi-modal medical imaging are example aspects that lead to more advanced image processing algorithms and the corresponding platforms on which they have to be executed. In this paper, we investigate the applicability of commercially available off-the-shelf components for a new computing platform. In the analysis, we will comply to some specific use cases. In cardiovascular minimal invasive surgery, physicians require low-latency imaging applications, as their actions must be directly visible on the screen. Typical image-processing algorithms in this domain are based on multi-resolution decomposition, noise reduction, image analysis and enhancement techniques. We have compared various solutions for possible processing architectures. The most interesting technology areas for constituting a new architecture are presented and we discuss the mapping of the use cases onto the various architectural proposals. Results show that a heterogeneous architecture gives the highest potential for current and upcoming image-processing applications. However, hardware and software solutions to support low-latency, high-bandwidth image streaming and an efficient concurrent distribution of functionality still need further development. This validates a clear direction for the future, which is based on modeling streaming computing architectures and special interconnect infrastructures.