Dealing with Label Scarcity in Computational Pathology: A Use Case in Prostate Cancer Classification

16 May 2019Koen DercksenWouter BultenGeert Litjens

Large amounts of unlabelled data are commonplace for many applications in computational pathology, whereas labelled data is often expensive, both in time and cost, to acquire. We investigate the performance of unsupervised and supervised deep learning methods when few labelled data are available... (read more)

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