Ms. Monica Gemo Profile

Monica Gemo

at Univ Catholique de Louvain

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Proceedings Article | 30 March 2007 Paper

A versatile knowledge-based clinical imaging annotation system for breast cancer screening

Monica Gemo, Annabelle Gouze, Benoît Debande, André Grivegnée, Gilbert Mazy, Benoît Macq

Proceedings Volume 6514, 65141U (2007) https://doi.org/10.1117/12.709522

KEYWORDS: Imaging systems, Breast cancer, Visualization, Multimedia, Diagnostics, Pathology, Feature extraction, Computing systems, Mammography, Medical imaging

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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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