156 citations · 344 across the 24 of their papers we have counts for
25 papers · 1 filter
SlideGraph+: Whole Slide Image Level Graphs to Predict HER2Status in Breast Cancer
Wenqi Lu, Michael Toss, Emad Rakha +2
Human epidermal growth factor receptor 2 (HER2) is an important prognostic and predictive factor which is overexpressed in 15-20% of breast cancer (BCa). The determination of its s…
Stain-Robust Mitotic Figure Detection for the Mitosis Domain Generalization Challenge
Mostafa Jahanifar, Adam Shephard, Neda Zamani Tajeddin +5
The detection of mitotic figures from different scanners/sites remains an important topic of research, owing to its potential in assisting clinicians with tumour grading. The MItos…
A QuadTree Image Representation for Computational Pathology
Rob Jewsbury, Abhir Bhalerao, Nasir Rajpoot
The field of computational pathology presents many challenges for computer vision algorithms due to the sheer size of pathology images. Histopathology images are large and need to…
Cells are Actors: Social Network Analysis with Classical ML for SOTA Histology Image Classification
Neda Zamanitajeddin, Mostafa Jahanifar, Nasir Rajpoot
Digitization of histology images and the advent of new computational methods, like deep learning, have helped the automatic grading of colorectal adenocarcinoma cancer (CRA). Prese…
Multiple Instance Captioning: Learning Representations from Histopathology Textbooks and Articles
Jevgenij Gamper, Nasir Rajpoot
We present ARCH, a computational pathology (CP) multiple instance captioning dataset to facilitate dense supervision of CP tasks. Existing CP datasets focus on narrow tasks; ARCH o…
Self-Path: Self-supervision for Classification of Pathology Images with Limited Annotations
Navid Alemi Koohbanani, Balagopal Unnikrishnan, Syed Ali Khurram +2
While high-resolution pathology images lend themselves well to `data hungry' deep learning algorithms, obtaining exhaustive annotations on these images is a major challenge. In thi…