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Proceedings Paper

Incorporating a segmentation routine for mammographic masses into a knowledge-based CADx approach
Author(s): Matthias Elter; Tobias Bergen
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Paper Abstract

Computer aided diagnosis (CADx) systems have the potential to support the radiologist in the complex task of discriminating benign and malignant types of breast lesions based on their appearance in mammograms. Previously, we have proposed a knowledge-based CADx approach for mammographic mass lesions using case-based reasoning. The input of the systems reasoning process are features that are automatically extracted from regions of interest (ROIs) depicting mammographic masses. However, despite the fact that the shape of a mass as well as the characteristics of its boundary are highly discriminative attributes for its diagnosis, we have not included shape and boundary features that are based on an explicit segmentation of the mass from the background tissue in the previously proposed CADx approach. Hence, we present a novel method for the segmentation of mammographic masses in this work and describe how we have integrated this segmentation module into our existent CADx system. The approach is based on the observation that the optical density of a mass is usually high near its core and decreases towards its boundary. Because of tissue superposition and the broad variety of appearances of masses, their automatic segmentation is a difficult task. Thus, it is not surprising that even after many years of research concerning the segmentation of masses no fully automatic approach that robustly solves the problem seems to exist. For this reason, we have included optional interactive modules in the proposed segmentation approach that allow fast and easy corrective interference of the radiologist with the segmentation process.

Paper Details

Date Published: 3 March 2009
PDF: 8 pages
Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 726025 (3 March 2009); doi: 10.1117/12.810981
Show Author Affiliations
Matthias Elter, Fraunhofer-Institut für Integrierte Schaltungen (Germany)
Tobias Bergen, Fraunhofer-Institut für Integrierte Schaltungen (Germany)


Published in SPIE Proceedings Vol. 7260:
Medical Imaging 2009: Computer-Aided Diagnosis
Nico Karssemeijer; Maryellen L. Giger, Editor(s)

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