articleIEEE Transactions on Medical ImagingFeb 12, 2016Closed access

AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images

German Center for Neurodegenerative Diseases · Technical University of Munich · +3 more institutions

PubMed
Indexed incrossrefpubmed

Abstract

The lack of publicly available ground-truth data has been identified as the major challenge for transferring recent developments in deep learning to the biomedical imaging domain. Though crowdsourcing has enabled annotation of large scale databases for real world images, its application for biomedical purposes requires a deeper understanding and hence, more precise definition of the actual annotation task. The fact that expert tasks are being outsourced to non-expert users may lead to noisy annotations introducing disagreement between users. Despite being a valuable resource for learning annotation models from crowdsourcing, conventional machine-learning methods may have difficulties dealing with noisy…

No related works found for this paper.