Using Ontologies in Formal Developments Targeting Certification

This is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this recordIFM 2019: 15th International Conference on integrated Formal Methods, 4-6 December 2019, Bergen, NorwayA common problem in the certification of highly safety or security critical systems is the consistency of the certification documentation in general and, in particular, the linking between semi-formal and formal content of the certification documentation. We address this problem by using an existing framework, Isabelle/DOF, that allows writing certification documents with consistency guarantees, in both, the semi-formal and formal parts. Isabelle/DOF supports the modeling of document ontologies using a strongly typed ontology definition language. An ontology is then enforced inside documents including formal parts, e.g., system models, verification proofs, code, tests and validations of corner-cases. The entire set of documents is checked within Isabelle/HOL, which includes the definition of ontologies and the editing of integrated documents based on them. This process is supported by an IDE that provides continuous checking of the document consistency. In this paper, we present how a specific software-engineering certification standard, namely CENELEC 50128, can be modeled inside Isabelle/DOF. Based on an ontology covering a substantial part of this standard, we present how Isabelle/DOF can be applied to a certification case-study in the railway domain.IRT System

Dynamic contrast-enhanced (DCE) imaging: state of the art and applications in whole-body imaging

Dynamic contrast-enhanced (DCE) imaging is a non-invasive technique used for the evaluation of tissue vascularity features through imaging series acquisition after contrast medium administration. Over the years, the study technique and protocols have evolved, seeing a growing application of this method across different imaging modalities for the study of almost all body districts. The main and most consolidated current applications concern MRI imaging for the study of tumors, but an increasing number of studies are evaluating the use of this technique also for inflammatory pathologies and functional studies. Furthermore, the recent advent of artificial intelligence techniques is opening up a vast scenario for the analysis of quantitative information deriving from DCE. The purpose of this article is to provide a comprehensive update on the techniques, protocols, and clinical applications – both established and emerging – of DCE in whole-body imaging