Initial Exploitation of the SONNET Derived Taxonomy of Mammographic Parenchymal Patterns

A taxonomy of mammography patterns has a number of potential uses which are discussed in this paper. The paper also presents further details about an organization of the mammography archive that was achieved by means of the SONNET self-organizing neural network. Preliminary results on the possible use of the mammography taxonomy to detect cancerous lesions via asymmetry identification are presented. A SONNET hierarchy capable of classifying parenchyma sub-types which combines with evolutionary computation is proposed which may overcome the challenging problem of the search for multiscale features over a diverse set of mammograms.