Using Linked Data and Web APIs for Automating the Pre-processing of Medical Images

Current developments in the health care sector are marked by the increased digitalisation of patient records, the use of electronic devices as supporting tools in patient care, and the employment of sensors (e.g. monitoring devices and surgery recording devices), which contribute directly to the abundance of medical data. However, before any significant benefits can be derived based on these growing data volumes and sources, challenges such as data format heterogeneity, distribution of the data sets, interoperability issues and basic pre-processing have to be addressed. In this paper we present an approach and a concrete architecture that support data consolidation and integration based on Linked Data principles. Furthermore, our solution enables the exible composition and execution of data processing pipelines, based on individual processing steps, exposed through semantically described Web APIs. We demonstrate the applicability of our approach by implementing a specific scenario - Brain Tumour Progression Maps, evaluating the performance of the distributed Web API-based solution in comparison to a local execution, and determining the coverage of derived requirements.