10 citations · 20 across the 4 of their papers we have counts for
4 papers
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…
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…
Mitosis Detection, Fast and Slow: Robust and Efficient Detection of Mitotic Figures
Mostafa Jahanifar, Adam Shephard, Neda Zamanitajeddin +4
Counting of mitotic figures is a fundamental step in grading and prognostication of several cancers. However, manual mitosis counting is tedious and time-consuming. In addition, va…
Cells are Actors: Social Network Analysis with Classical ML for SOTA Histology Image Classification
Neda Zamanitajeddin, Mostafa Jahanifar, Nasir Rajpoot
Digitization of histology images and the advent of new computational methods, like deep learning, have helped the automatic grading of colorectal adenocarcinoma cancer (CRA). Prese…