Abstract
Today, clinicians rely more and more on medical images for screening, diagnosis, treatment planning, and follow-up examinations. While medical images provide a wealth of information for clinicians, content information cannot be automatically integrated into advanced medical applications such as those for the clinical decision support. The implementation of advanced medical applications requires means for the automated post-processing of medical image annotations. In this article we describe how we made use of reasoning technologies to post-process medical image annotations in the context of the automated staging process of lymphoma patients. First, we describe how automatic anatomy detectors and OWL reasoning processes can be used to preprocess medical images automatically and in a way that makes accurate input to further, more complex reasoning processes possible. Second, we enhance and integrate patients’ image metadata by formalized practical clinical knowledge sources. The resulting combined data serve as input to an automatic reasoning process in order to stage lymphoma patients automatically.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Network Modeling Analysis in Health Informatics and Bioinformatics
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.