10 citations · 30 across the 14 of their papers we have counts for
15 papers
Explainable Artificial Intelligence (XAI) in Computational Pathology: Definitions, Taxonomy, and Recommendations
Shubham Innani, Suhang You, Adam Shephard +13
Computational pathology (CompPath) is transforming medicine by leveraging artificial intelligence (AI) algorithms to support diagnosis, prognosis, and treatment prediction from gig…
Multimodal Oncology Agent for IDH1 Mutation Prediction in Low-Grade Glioma
Hafsa Akebli, Adam Shephard, Vincenzo Della Mea +1
Low-grade gliomas frequently present IDH1 mutations that define clinically distinct subgroups with specific prognostic and therapeutic implications. This work introduces a Multimod…
CORE -- A Cell-Level Coarse-to-Fine Image Registration Engine for Multi-stain Image Alignment
Esha Sadia Nasir, Behnaz Elhaminia, Mark Eastwood +9
Accurate and efficient registration of whole slide images (WSIs) is essential for high-resolution, nuclei-level analysis in multi-stained tissue slides. We propose a novel coarse-t…
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…
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…
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…
Domain generalization across tumor types, laboratories, and species -- insights from the 2022 edition of the Mitosis Domain Generalization Challenge
Marc Aubreville, Nikolas Stathonikos, Taryn A. Donovan +27
Recognition of mitotic figures in histologic tumor specimens is highly relevant to patient outcome assessment. This task is challenging for algorithms and human experts alike, with…
A Fully Automated and Explainable Algorithm for the Prediction of Malignant Transformation in Oral Epithelial Dysplasia
Adam J Shephard, Raja Muhammad Saad Bashir, Hanya Mahmood +11
Oral epithelial dysplasia (OED) is a premalignant histopathological diagnosis given to lesions of the oral cavity. Its grading suffers from significant inter-/intra- observer varia…
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…
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting
Simon Graham, Quoc Dang Vu, Mostafa Jahanifar +86
Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovatio…
Mitosis Detection, Fast and Slow: Robust and Efficient Detection of Mitotic Figures
Mostafa Jahanifar, Adam Shephard, Neda Zamanitajeddin +4
Counting of mitotic figures is a fundamental step in grading and prognostication of several cancers. However, manual mitosis counting is tedious and time-consuming. In addition, va…
TIAger: Tumor-Infiltrating Lymphocyte Scoring in Breast Cancer for the TiGER Challenge
Adam Shephard, Mostafa Jahanifar, Ruoyu Wang +6
The quantification of tumor-infiltrating lymphocytes (TILs) has been shown to be an independent predictor for prognosis of breast cancer patients. Typically, pathologists give an e…
Cellular Segmentation and Composition in Routine Histology Images using Deep Learning
Muhammad Dawood, Raja Muhammad Saad Bashir, Srijay Deshpande +2
Identification and quantification of nuclei in colorectal cancer haematoxylin \& eosin (H\&E) stained histology images is crucial to prognosis and patient management. In computatio…
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…