1 citations · 1 across the 2 of their papers we have counts for
5 papers
KongNet: A Multi-headed Deep Learning Model for Detection and Classification of Nuclei in Histopathology Images
Jiaqi Lv, Esha Sadia Nasir, Kesi Xu +4
Accurate detection and classification of nuclei in histopathology images are critical for diagnostic and research applications. We present KongNet, a multi-headed deep learning arc…
Potential Role of Agentic Artificial Intelligence in Toxicologic Pathology
Nasir Rajpoot, Richard Haworth, Xavier Palazzi +14
As the volume and complexity of nonclinical toxicology studies continue to increase, toxicologic pathology reporting faces persistent challenges, including fragmented sources of da…
Benchmarking Domain Generalization Algorithms in Computational Pathology
Neda Zamanitajeddin, Mostafa Jahanifar, Kesi Xu +2
Deep learning models have shown immense promise in computational pathology (CPath) tasks, but their performance often suffers when applied to unseen data due to domain shifts. Addr…
MitoDetect++: A Domain-Robust Pipeline for Mitosis Detection and Atypical Subtyping
Esha Sadia Nasir, Jiaqi Lv, Mostafa Jahanifar +1
Automated detection and classification of mitotic figures especially distinguishing atypical from normal remain critical challenges in computational pathology. We present MitoDetec…
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…