activity
20182023
most citedPanNuke Dataset Extension, Insights and Baselines

156 citations · 178 across the 6 of their papers we have counts for

collaborators

8 papers

eess.IV2023

An Automated Pipeline for Tumour-Infiltrating Lymphocyte Scoring in Breast Cancer

Adam J Shephard, Mostafa Jahanifar, Ruoyu Wang +6

Tumour-infiltrating lymphocytes (TILs) are considered as a valuable prognostic markers in both triple-negative and human epidermal growth factor receptor 2 (HER2) positive breast c…

eess.IV202219 cited

On Smart Gaze based Annotation of Histopathology Images for Training of Deep Convolutional Neural Networks

Komal Mariam, Osama Mohammed Afzal, Wajahat Hussain +5

Unavailability of large training datasets is a bottleneck that needs to be overcome to realize the true potential of deep learning in histopathology applications. Although slide di…

cs.CV20211 cited

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…

eess.IV20212 cited

Simultaneous Nuclear Instance and Layer Segmentation in Oral Epithelial Dysplasia

Adam J. Shephard, Simon Graham, R. M. Saad Bashir +4

Oral epithelial dysplasia (OED) is a pre-malignant histopathological diagnosis given to lesions of the oral cavity. Predicting OED grade or whether a case will transition to malign…

eess.IV2021

A digital score of tumour-associated stroma infiltrating lymphocytes predicts survival in head and neck squamous cell carcinoma

Muhammad Shaban, Shan E Ahmed Raza, Mariam Hassan +11

The infiltration of T-lymphocytes in the stroma and tumour is an indication of an effective immune response against the tumour, resulting in better survival. In this study, our aim…

cs.CV2020

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…