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dc.contributor.author Chikontwe, Philip ko
dc.contributor.author Kim, Meejeong ko
dc.contributor.author Nam, Soojeong ko
dc.contributor.author Go, Heounjeong ko
dc.contributor.author Park, Sang Hyun ko
dc.date.accessioned 2021-01-29T07:23:13Z -
dc.date.available 2021-01-29T07:23:13Z -
dc.date.created 2020-10-29 -
dc.date.issued 2020-10-05 -
dc.identifier.citation International Conference on Medical Image Computing and Computer Assisted Interventions, pp.519 - 528 -
dc.identifier.isbn 9783030597214 -
dc.identifier.issn 0302-9743 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/12873 -
dc.description.abstract Histopathology image analysis plays an important role in the treatment and diagnosis of cancer. However, analysis of whole slide images (WSI) with deep learning is challenging given that the duration of pixel-level annotations is laborious and time consuming. To address this, recent methods have considered WSI classification as a Multiple Instance Learning (MIL) problem often with a multi-stage process for learning instance and slide level features. Currently, most methods focus on either instance-selection or instance prediction-aggregation that often fails to generalize and ignores instance relations. In this work, we propose a MIL-based method to jointly learn both instance- and bag-level embeddings in a single framework. In addition, we propose a center loss that maps embeddings of instances from the same bag to a single centroid and reduces intra-class variations. Consequently, our model can accurately predict instance labels and leverages robust hierarchical pooling of features to obtain bag-level features without sacrificing accuracy. Experimental results on curated colon datasets show the effectiveness of the proposed methods against recent state-of-the-art methods. © 2020, Springer Nature Switzerland AG. -
dc.language English -
dc.publisher Springer Science and Business Media Deutschland GmbH -
dc.title Multiple Instance Learning with Center Embeddings for Histopathology Classification -
dc.type Conference -
dc.identifier.doi 10.1007/978-3-030-59722-1_50 -
dc.identifier.scopusid 2-s2.0-85092733064 -
dc.type.local Article(Overseas) -
dc.type.rims CONF -
dc.description.journalClass 1 -
dc.contributor.localauthor Park, Sang Hyun -
dc.contributor.nonIdAuthor Kim, Meejeong -
dc.contributor.nonIdAuthor Nam, Soojeong -
dc.contributor.nonIdAuthor Go, Heounjeong -
dc.identifier.citationStartPage 519 -
dc.identifier.citationEndPage 528 -
dc.identifier.citationTitle International Conference on Medical Image Computing and Computer Assisted Interventions -
dc.identifier.conferencecountry PE -
dc.identifier.conferencelocation Lima -


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