Scalable Digital Pathology Platform Over Standard Cloud Native Technologies

Abstract

The use of digital imaging in medicine has become a cornerstone of modern diagnosis and treatment processes. The new technologies available in this ecosystem allowed healthcare institutions to improve their workflows, data access, sharing, and visualization using standardized formats. The migration of these services to the cloud enables a remote diagnostic environment, where professionals can review the studies remotely and engage in collaborative sessions. Despite the advantages of cloud-ready environments, their adoption has been slowed down by the demanding scenario high-resolution medical images pose. Some studies can have several gigabytes of data that need to be managed and consumed in the network. In this context, performance constraints of the software platforms can result in severe denial of clinical service. This work proposes a highly scalable cloud platform for extreme medical imaging scenarios. It provides scalability with auto-scaling mechanisms that allow dynamic adjustment of computational resources according to the service load.