Abstract
This paper deals with learning spiculation scores of masses in a supervised manner. Three spiculation score prediction models treating the score either as a continuous or ordinary variable are presented. These models were compared on a data-set of 255 masses.
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Stainvas, I., Stoeckel, J., Ratner, E., Abramov, M., Lederman, R. (2010). Towards Learning Spiculation Score of the Masses in Mammography Images. 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_37
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DOI: https://doi.org/10.1007/978-3-642-13666-5_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13665-8
Online ISBN: 978-3-642-13666-5
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