Publications (4)
From Explainable to Explained AI: Ideas for Falsifying and Quantifying Explanations
Yoni Schirris, Eric Marcus, Jonas Teuwen +2
Explaining deep learning models is essential for clinical integration of medical image analysis systems. A good explanation highlights if a model depends on spurious features that…
ECTIL: Label-efficient Computational Tumour Infiltrating Lymphocyte (TIL) assessment in breast cancer: Multicentre validation in 2,340 patients with breast cancer
Yoni Schirris, Rosie Voorthuis, Mark Opdam +18
The level of tumour-infiltrating lymphocytes (TILs) is a prognostic factor for patients with (triple-negative) breast cancer (BC). Computational TIL assessment (CTA) has the potent…
Sparse-shot Learning with Exclusive Cross-Entropy for Extremely Many Localisations
Andreas Panteli, Jonas Teuwen, Hugo Horlings +1
Object localisation, in the context of regular images, often depicts objects like people or cars. In these images, there is typically a relatively small number of objects per class…
Foundation Models in Medical Imaging: A Review and Outlook
Vivien van Veldhuizen, Vanessa Botha, Chunyao Lu +10
Foundation models (FMs) are changing the way medical images are analyzed by learning from large collections of unlabeled data. Instead of relying on manually annotated examples, FM…