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This article is part of the supplement: Proceedings of the 11th European Congress on Telepathology and 5th International Congress on Virtual Microscopy

Open Access Proceedings

Automated classification of breast cancer morphology in histopathological images

Ville Ojansivu1*, Nina Linder1, Esa Rahtu2, Matti Pietikäinen2, Mikael Lundin1, Heikki Joensuu3 and Johan Lundin1

Author Affiliations

1 Institute for Molecular Medicine Finland-FIMM, Helsinki, Finland

2 University of Oulu, Center for Machine Vision Research, Oulu, Finland

3 Department of Oncology, Helsinki University Central Hospital, Helsinki, Finland

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Diagnostic Pathology 2013, 8(Suppl 1):S29  doi:10.1186/1746-1596-8-S1-S29

Published: 30 September 2013

First paragraph (this article has no abstract)

The morphology of a breast cancer tumour, as examined through an optical microscope, is currently assessed visually by the pathologist in parallel with making the cancer diagnosis. The grade of differentiation, which describes how closely the morphology of the tumour resembles the corresponding healthy tissue of an organ, is undisputedly related to the outcome of breast cancer [1]. However, tumour grade is largely regarded as an unreliable prognostic factor due to its poor reproducibility [2]. The visually determined morphology is afflicted with a poor inter- and intra observer agreement, which prevents grade from being fully utilized as an important outcome predictor. The same pathologist may assign different grade to the same tumour when assessment is repeated, and different pathologists disagree to a substantial level when assessing the same tumour [3].