ABSTRACT
In line with its vision to further develop medical imaging via cloud computation and advanced analytics, the company launched its effort to explore big data and machine learning to advance the state of the art of medical image processing and automation. From a background in applying computational fluid dynamics to Computed tomography scans for sleep apnea, the team had built a cloud-based tool to perform advanced analyses of large image sets, but they realized over time that imaging alone was not sufficient to determine treatment for apnea patients. The team had been hearing about deep learning, a nascent technology that was revolutionizing computer vision. The decision was made to combine the two technologies to process 4D Flow images in the cloud. A team of engineers began planning software that would manage security. Very quickly, the option of attempting to create a hyper-secure cloud was deemed unattractive.
