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20212026
most citedDomain Generalization in Computational Pathology: Survey and Guidelines

10 citations · 30 across the 14 of their papers we have counts for

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Showing 2023Show all

7 papers · 1 filter

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.IV2023★ 1 cited

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…

eess.IV2023★ 10 cited

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…

cs.CV2023★ 2 cited

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…

q-bio.QM2023

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…

cs.CV2023★ 1 cited

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…

cs.CV2023★ 1 cited

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…