Initial exploitation of the SONNET derived taxonomy of mammographic parenchymal patterns

Daniel Howard, Simon C. Roberts, Adrian Brezulianu, Conor Ryan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of the Frontiers in the Convergence of Bioscience and Information Technologies, FBIT 2007
Pages390-395
Number of pages6
DOIs
Publication statusPublished - 2007
EventFrontiers in the Convergence of Bioscience and Information Technologies, FBIT 2007 - Jeju Island, Korea, Republic of
Duration: 11 Oct 200713 Oct 2007

Publication series

NameProceedings of the Frontiers in the Convergence of Bioscience and Information Technologies, FBIT 2007

Conference

ConferenceFrontiers in the Convergence of Bioscience and Information Technologies, FBIT 2007
Country/TerritoryKorea, Republic of
CityJeju Island
Period11/10/0713/10/07

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