480 citations · 651 across the 11 of their papers we have counts for
13 papers
TIAViz: A Browser-based Visualization Tool for Computational Pathology Models
Mark Eastwood, John Pocock, Mostafa Jahanifar +8
Digital pathology has gained significant traction in modern healthcare systems. This shift from optical microscopes to digital imagery brings with it the potential for improved dia…
On generalisability of segment anything model for nuclear instance segmentation in histology images
Kesi Xu, Lea Goetz, Nasir Rajpoot
Pre-trained on a large and diverse dataset, the segment anything model (SAM) is the first promptable foundation model in computer vision aiming at object segmentation tasks. In thi…
Transformer-based Model for Oral Epithelial Dysplasia Segmentation
Adam J Shephard, Hanya Mahmood, Shan E Ahmed Raza +12
Oral epithelial dysplasia (OED) is a premalignant histopathological diagnosis given to lesions of the oral cavity. OED grading is subject to large inter/intra-rater variability, re…
Domain Generalization in Computational Pathology: Survey and Guidelines
Mostafa Jahanifar, Manahil Raza, Kesi Xu +8
Deep learning models have exhibited exceptional effectiveness in Computational Pathology (CPath) by tackling intricate tasks across an array of histology image analysis application…
Unsupervised Mutual Transformer Learning for Multi-Gigapixel Whole Slide Image Classification
Sajid Javed, Arif Mahmood, Talha Qaiser +2
Classification of gigapixel Whole Slide Images (WSIs) is an important prediction task in the emerging area of computational pathology. There has been a surge of research in deep le…
Why is the winner the best?
Matthias Eisenmann, Annika Reinke, Vivienn Weru +122
International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to in…