1 citations · 1 across the 3 of their papers we have counts for
4 papers
A Smaller Transformer in Your Transformer
Dhananjay Tomar, Marius Aasan, Andreas Kleppe +1
Recent findings indicate that Vision Transformers settle into locally similar computational phases, implying a level of depthwise computational redundancy. However, existing method…
Enabling clinical use of foundation models for computational pathology
Audun L Henriksen, Ole-Johan Skrede, Lisa van der Schee +31
Foundation models for computational pathology are expected to facilitate the development of high-performing, generalisable deep learning systems. However, in addition to biological…
Generalisation of automatic tumour segmentation in histopathological whole-slide images across multiple cancer types
Ole-Johan Skrede, Manohar Pradhan, Maria Xepapadakis Isaksen +20
Deep learning is expected to aid pathologists by automating tasks such as tumour segmentation. We aimed to develop one universal tumour segmentation model for histopathological ima…
Are nuclear masks all you need for improved out-of-domain generalisation? A closer look at cancer classification in histopathology
Dhananjay Tomar, Alexander Binder, Andreas Kleppe
Domain generalisation in computational histopathology is challenging because the images are substantially affected by differences among hospitals due to factors like fixation and s…