Topological Connected Chain Modelling for Classification of Mammographic Microcalcification

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dc.contributor.authorGeorge, Minuen_US
dc.contributor.authorDenton, Erika R. E.en_US
dc.contributor.authorZwiggelaar, Reyeren_US
dc.contributor.editor{Tam, Gary K. L. and Vidal, Francken_US
dc.date.accessioned2018-09-19T15:15:01Z
dc.date.available2018-09-19T15:15:01Z
dc.date.issued2018
dc.description.abstractBreast cancer continues to be the most common type of cancer among women. Early detection of breast cancer is key to effective treatment. The presence of clusters of fine, granular microcalcifications in mammographic images can be a primary sign of breast cancer. The malignancy of any cluster of microcalcification cannot be reliably determined by radiologists from mammographic images and need to be assessed through histology images. In this paper, a novel method of mammographic microcalcification classification is described using the local topological structure of microcalcifications. Unlike the statistical and texture features of microcalcifications, the proposed method focuses on the number of microcalcifications in local clusters, the distance between them, and the number of clusters. The initial evaluation on the Digital Database for Screening Mammography (DDSM) database shows promising results with 86% accuracy and findings which are in line with clinical perception of benign and malignant morphological appearance of microcalcification clusters.en_US
dc.description.sectionheadersVision and Learning
dc.description.seriesinformationComputer Graphics and Visual Computing (CGVC)
dc.identifier.doi10.2312/cgvc.20181201
dc.identifier.isbn978-3-03868-071-0
dc.identifier.pages1-5
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/cgvc20181201
dc.identifier.urihttps://doi.org/10.2312/cgvc.20181201
dc.publisherThe Eurographics Associationen_US
dc.subjectmicrocalcification classification
dc.subjectbenign/malignant
dc.subjecttopological modelling
dc.subjectgraph connected chain
dc.titleTopological Connected Chain Modelling for Classification of Mammographic Microcalcificationen_US
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Computer Graphics & Visual Computing (CGVC) 2018