Abstract
In this work we study how the BI-RADS assessment could help to improve the performance of a CAD (Computer Aided Diagnosis) image-based system in the task of masses diagnosis. Our system is based on the use of Independent Component Analysis (ICA) as feature extractor from mammographic images, and Neural Networks as a final classifier. For our tests, the “Digital Database for Screening Mammography” (DDSM) has been used, particularly the subset BCRP_MASS1. The best results were obtained when we used the image data (with feature extraction by means of ICA) together with the BI-RADS assessment provided by DDSM database.
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García-Manso, A., García-Orellana, C.J., Gallardo-Caballero, R., González-Velasco, H., Macías-Macías, M. (2010). Effect of BI-RADS Assessment in Improving CAD of Masses. In: Martí, J., Oliver, A., Freixenet, J., Martí, R. (eds) Digital Mammography. IWDM 2010. Lecture Notes in Computer Science, vol 6136. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13666-5_83
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DOI: https://doi.org/10.1007/978-3-642-13666-5_83
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