3 citations · 7 across the 11 of their papers we have counts for
11 papers
Hard Negative Sample Mining for Whole Slide Image Classification
Wentao Huang, Xiaoling Hu, Shahira Abousamra +2
Weakly supervised whole slide image (WSI) classification is challenging due to the lack of patch-level labels and high computational costs. State-of-the-art methods use self-superv…
Semi-Supervised Contrastive VAE for Disentanglement of Digital Pathology Images
Mahmudul Hasan, Xiaoling Hu, Shahira Abousamra +3
Despite the strong prediction power of deep learning models, their interpretability remains an important concern. Disentanglement models increase interpretability by decomposing th…
RadGazeGen: Radiomics and Gaze-guided Medical Image Generation using Diffusion Models
Moinak Bhattacharya, Gagandeep Singh, Shubham Jain +1
In this work, we present RadGazeGen, a novel framework for integrating experts' eye gaze patterns and radiomic feature maps as controls to text-to-image diffusion models for high f…
Histo-Diffusion: A Diffusion Super-Resolution Method for Digital Pathology with Comprehensive Quality Assessment
Xuan Xu, Saarthak Kapse, Prateek Prasanna
Digital pathology has advanced significantly over the last decade, with Whole Slide Images (WSIs) encompassing vast amounts of data essential for accurate disease diagnosis. High-r…
Automated Assessment of Critical View of Safety in Laparoscopic Cholecystectomy
Yunfan Li, Himanshu Gupta, Haibin Ling +4
Cholecystectomy (gallbladder removal) is one of the most common procedures in the US, with more than 1.2M procedures annually. Compared with classical open cholecystectomy, laparos…
Attention De-sparsification Matters: Inducing Diversity in Digital Pathology Representation Learning
Saarthak Kapse, Srijan Das, Jingwei Zhang +4
We propose DiRL, a Diversity-inducing Representation Learning technique for histopathology imaging. Self-supervised learning techniques, such as contrastive and non-contrastive app…