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20242026
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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…

eess.IV2024

TIAViz: A Browser-based Visualization Tool for Computational Pathology Models

Mark Eastwood, John Pocock, Mostafa Jahanifar +8

Digital pathology has gained significant traction in modern healthcare systems. This shift from optical microscopes to digital imagery brings with it the potential for improved dia…

eess.IV20231 cited

Transformer-based Model for Oral Epithelial Dysplasia Segmentation

Adam J Shephard, Hanya Mahmood, Shan E Ahmed Raza +12

Oral epithelial dysplasia (OED) is a premalignant histopathological diagnosis given to lesions of the oral cavity. OED grading is subject to large inter/intra-rater variability, re…

eess.IV2023

Cell Maps Representation For Lung Adenocarcinoma Growth Patterns Classification In Whole Slide Images

Arwa Al-Rubaian, Gozde N. Gunesli, Wajd A. Althakfi +3

Lung adenocarcinoma is a morphologically heterogeneous disease, characterized by five primary histologic growth patterns. The quantity of these patterns can be related to tumor beh…

eess.IV202310 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…