Abstract
In the field of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of breast cancer, current research efforts in computer-aided diagnosis (CADx) are mainly focused on the temporal series of T 1-weighted images acquired during uptake of a contrast agent, processing morphological and kinetic information. Although static T 2-weighted images are usually part of DCE-MRI protocols, they are seldom used in CADx systems. The aim of this work was to evaluate to what extent T 2-weighted images provide complementary information to a CADx system, improving its performance for the task of discriminating benign breast masses from life-threatening carcinomas. In a preliminary study considering 64 masses, inclusion of lesion features derived from T 2-weighted images increased the classification performance from A z =0.94 to A z =0.99.
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van Aalst, W., Twellmann, T., Buurman, H., Gerritsen, F.A., ter Haar Romeny, B.M. (2008). Computer-Aided Diagnosis in Breast MRI: Do Adjunct Features Derived from T 2-weighted Images Improve Classification of Breast Masses?. In: Tolxdorff, T., Braun, J., Deserno, T.M., Horsch, A., Handels, H., Meinzer, HP. (eds) Bildverarbeitung für die Medizin 2008. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78640-5_3
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DOI: https://doi.org/10.1007/978-3-540-78640-5_3
Publisher Name: Springer, Berlin, Heidelberg
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