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20182024
most citedPanNuke Dataset Extension, Insights and Baselines

156 citations · 187 across the 15 of their papers we have counts for

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Showing eess.IVShow all

9 papers · 1 filter

eess.IV2024★ 1 cited

Whole Slide Image Classification of Salivary Gland Tumours

John Charlton, Ibrahim Alsanie, Syed Ali Khurram

This work shows promising results using multiple instance learning on salivary gland tumours in classifying cancers on whole slide images. Utilising CTransPath as a patch-level fea…

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

LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset

Yiping Jiao, Jeroen van der Laak, Shadi Albarqouni +18

We introduce LYSTO, the Lymphocyte Assessment Hackathon, which was held in conjunction with the MICCAI 2019 Conference in Shenzen (China). The competition required participants to…

eess.IV2022★ 5 cited

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…

eess.IV2022★ 19 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…

eess.IV2021★ 2 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…

eess.IV2020★ 156 cited

PanNuke Dataset Extension, Insights and Baselines

Jevgenij Gamper, Navid Alemi Koohbanani, Ksenija Benes +6

The emerging area of computational pathology (CPath) is ripe ground for the application of deep learning (DL) methods to healthcare due to the sheer volume of raw pixel data in who…