Cloud-based adaptive compression and secure management services for 3D healthcare data

Several studies show that the lack of access to resources and shared data is one of the main causes of errors in the healthcare sector. In particular, 3D medical images play a fundamental role in healthcare environment, but they are typically very large in size. Therefore, their management, which should be performed also by means of devices with limited characteristics, requires complex network protocols along with advanced compression and security techniques. This work concerns the secure management of 3D medical images, with the main aim that such management must take place in an almost completely transparent manner for the end-user, regardless of the computational and networking capabilities he may use. In particular, our contribution is twofold: first, we propose an engine for lossless dynamic and adaptive compression of 3D medical images, which also allows the embedding of security watermarks within them. Furthermore, in order to provide effective, secure and flexible access to healthcare resources that need to be managed by medical applications, we define the architecture of a SaaS Cloud system, which is based on the aforementioned engine. The resulting architecture allows devices with totally different and heterogeneous hardware and software characteristics to interact among them, so that these differences are almost completely transparent to the end-user. A Cloud-based solution for lossless dynamic and adaptive compression of 3D medical images.Management of such data may be considered as an atypical Big Data problem.It provides SaaS services based on an elastic and on-demand peer to peer overlay infrastructure.It also provides effective, secure and flexible access to healthcare resources that need to be managed by medical applications.Allows devices with totally different and heterogeneous hardware and software characteristics to interact among them.