  Machine learning and artificial intelligence have shown remarkable
performance in accelerated magnetic resonance imaging (MRI). Cloud computing
technologies have great advantages in building an easily accessible platform to
deploy advanced algorithms. In this work, we develop an open-access,
easy-to-use and high-performance medical intelligence cloud computing platform
(XCloud-pFISTA) to reconstruct MRI images from undersampled k-space data. Two
state-of-the-art approaches of the Projected Fast Iterative Soft-Thresholding
Algorithm (pFISTA) family have been successfully implemented on the cloud. This
work can be considered as a good example of cloud-based medical image
reconstruction and may benefit the future development of integrated
reconstruction and online diagnosis system.
