Medical information is evolving towards more complex multimedia data representation, as new imaging modalities
are made available by sophisticated devices. Features such as segmented lesions can now be extracted through
analysis techniques and need to be integrated into clinical patient data. The management of structured information
extracted from multimedia has been addressed in knowledge based annotation systems providing methods
to attach interpretative semantics to multimedia content. Building on these methods, we develop a new clinical
imaging annotation system for computer aided breast cancer screening. The proposed system aims at more
consistent, efficient and standardised data mark-up of digital and digitalised radiology images. The objective is
to provide detailed characterisation of abnormalities as an aid in the diagnostic task through integrated annotation
management. The system combines imaging analysis results and radiologist diagnostic information about
suspicious findings by mapping well-established visual and low-level descriptors into pathology specific profiles.
The versatile characterisation allows differentiating annotation descriptors for different types of findings. Our
approach of semi-automatic integrated annotations supports increased quality assurance in screening practice.
This is achieved through detailed and objective patient imaging information while providing user-friendly means
for their manipulation that is oriented to relieving the radiologist's workload.
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