3 papers
eess.IV2026
Computationally Efficient Pathology Segmentation using Knowledge Distillation from Foundation Models
Jiaqi Lv, Yijie Zhu, Saki Okada +4
Automatic tissue segmentation is essential for large-scale analysis of histopathology whole-slide images (WSIs), but accurate pixel-level segmentation remains challenging. Pixel-le…
eess.IV2025
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…
cs.CV2024
Nuclei-Location Based Point Set Registration of Multi-Stained Whole Slide Images
Adith Jeyasangar, Abdullah Alsalemi, Shan E Ahmed Raza
Whole Slide Images (WSIs) provide exceptional detail for studying tissue architecture at the cell level. To study tumour microenvironment (TME) with the context of various protein…