Impact of advanced parallel or cloud computing technologies for image guided diagnosis and therapy.

Medical imaging technology has revolutionized health care for a long time. The past decade has witnessed considerable advancements in imaging techniques, developing from structural to functional or from static to dynamic, which enabled both individualand population-based analysis. While the number of multimodality imaging-based diagnoses and procedures is increasing considerably, effective, safe, and high speed/quality imaging is important for much medical decision-making. However, it’s impossible to realize these standards free from powerful computing technologies. Image processing with graphics processing unit (GPU)-based parallel computing technique is an alternative way to solve image processing problems in multimodality image diagnoses and telemedicine, which require large times of processing as well as handling large amounts of information in “acceptable time”. Cloud computing has been introduced only recently but is already one of the major topics of discussion in research and clinical settings. The provision of extensive, easily accessible, and reconfigurable resources such as virtual systems, platforms, and applications with low service cost has caught the attention of many researchers and clinicians. However, it is still in its infancy in the medical imaging domain, and there is currently low market penetration within the field. This situation may change rapidly in the near future. Among the potential driving forces for the increased use of cloud computing in medical imaging are raw data management and image processing and sharing demands, all of which require high-capacity data storage and computing. With the development of high speed/quality imaging technologies, medical imaging societies have to embrace parallel and/or cloud computing technologies and use them as a powerful tool to enhance the efficiency and accuracy of multimodality imaging data analysis. In this special issue, we invite the latest research works from both academia and practitioners to share experiences and ideas on how best we could make use of advanced parallel or cloud computing