Geert Litjens

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

2019 · arXiv (Cornell University)

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 …

End-to-end classification on basal-cell carcinoma histopathology whole-slides images

2021

The high incidence of BCC skin cancer caused that the amount of work for pathologists has risen to unprecedented levels. Acquiring outlined annotations for training deep learning models classifying BCC is often tedious and time …