Abstract
Computer-aided detection systems have as aim the increase of detection rates when analysing mammograms, by identifying features that are characteristic for breast cancer. In this research we aimed at using the features extracted from mammographic images in order to analyse the development of suspicious lesions. Different from other approaches, we based our data modelling on object orientation. This allowed not only for a description of domain entities and their intrinsic relationships, but also for the application of relational probabilistic techniques, which can handle heterogeneous data instances both in terms of learning and inference.
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Ferreira, N., Lucas, P.J.F. (2009). Modelling Screening Mammography Images: A Probabilistic Relational Approach. In: Combi, C., Shahar, Y., Abu-Hanna, A. (eds) Artificial Intelligence in Medicine. AIME 2009. Lecture Notes in Computer Science(), vol 5651. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02976-9_57
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DOI: https://doi.org/10.1007/978-3-642-02976-9_57
Publisher Name: Springer, Berlin, Heidelberg
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