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eess.IV2025★ 1 cited
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…
eess.IV2024★ 1 cited
On generalisability of segment anything model for nuclear instance segmentation in histology images
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. In thi…
eess.IV2023★ 10 cited
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…