Search Results for author: Kesi Xu

Found 2 papers, 0 papers with code

On generalisability of segment anything model for nuclear instance segmentation in histology images

no code implementations25 Jan 2024 Kesi Xu, Lea Goetz, Nasir Rajpoot

Pre-trained on a large and diverse dataset, the segment anything model (SAM) is the first promptable foundation model in computer vision aiming at object segmentation tasks.

Instance Segmentation Segmentation +2

Domain Generalization in Computational Pathology: Survey and Guidelines

no code implementations30 Oct 2023 Mostafa Jahanifar, Manahil Raza, Kesi Xu, Trinh Vuong, Rob Jewsbury, Adam Shephard, Neda Zamanitajeddin, Jin Tae Kwak, Shan E Ahmed Raza, Fayyaz Minhas, Nasir Rajpoot

Deep learning models have exhibited exceptional effectiveness in Computational Pathology (CPath) by tackling intricate tasks across an array of histology image analysis applications.

Benchmarking Domain Generalization

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