8 citations · 9 across the 6 of their papers we have counts for
6 papers
Mitosis Detection in the Wild: Multi-Tumor and Context-Aware Generalization in the MIDOG 2025 Challenge
Marc Aubreville, Jonas Ammeling, Sweta Banerjee +64
Automated mitosis detection is a well-established task in computational pathology. While previous benchmarks focused on scanner-induced domain shift, clinical "real-world" applicat…
A deep learning framework for glomeruli segmentation with boundary attention
Behnaz Elhaminia, Catherine King, Jiaqi Lv +5
Accurate detection and segmentation of glomeruli in kidney tissue are essential for diagnostic applications. Traditional deep learning methods primarily rely on semantic segmentati…
ModalSurv: Investigating opportunities and limitations of multimodal deep survival learning in prostate and bladder cancer
Noorul Wahab, Ethar Alzaid, Jiaqi Lv +3
Accurate survival prediction is essential for personalised cancer treatment. We propose ModalSurv, a multimodal deep survival framework integrating clinical, MRI, histopathology, a…
From Traditional to Deep Learning Approaches in Whole Slide Image Registration: A Methodological Review
Behnaz Elhaminia, Abdullah Alsalemi, Esha Nasir +6
Whole slide image (WSI) registration is an essential task for analysing the tumour microenvironment (TME) in histopathology. It involves the alignment of spatial information betwee…
HoVer-Net: Simultaneous Segmentation and Classification of Nuclei in Multi-Tissue Histology Images
Simon Graham, Quoc Dang Vu, Shan E Ahmed Raza +4
Nuclear segmentation and classification within Haematoxylin & Eosin stained histology images is a fundamental prerequisite in the digital pathology work-flow. The development of au…
DeepSDCS: Dissecting cancer proliferation heterogeneity in Ki67 digital whole slide images
Priya Lakshmi Narayanan, Shan E Ahmed Raza, Andrew Dodson +3
Ki67 is an important biomarker for breast cancer. Classification of positive and negative Ki67 cells in histology slides is a common approach to determine cancer proliferation stat…