156 citations · 187 across the 15 of their papers we have counts for
15 papers
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…
An Attention Based Pipeline for Identifying Pre-Cancer Lesions in Head and Neck Clinical Images
Abdullah Alsalemi, Anza Shakeel, Mollie Clark +2
Early detection of cancer can help improve patient prognosis by early intervention. Head and neck cancer is diagnosed in specialist centres after a surgical biopsy, however, there…
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…
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…
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…
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…
Rank the triplets: A ranking-based multiple instance learning framework for detecting HPV infection in head and neck cancers using routine H&E images
Ruoyu Wang, Syed Ali Khurram, Amina Asif +2
The aetiology of head and neck squamous cell carcinoma (HNSCC) involves multiple carcinogens such as alcohol, tobacco and infection with human papillomavirus (HPV). As the HPV infe…
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…
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…
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…
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…
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…
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…
Methods for Segmentation and Classification of Digital Microscopy Tissue Images
Quoc Dang Vu, Simon Graham, Minh Nguyen Nhat To +11
High-resolution microscopy images of tissue specimens provide detailed information about the morphology of normal and diseased tissue. Image analysis of tissue morphology can help…