5 papers
From Classification to Cross-Modal Understanding: Leveraging Vision-Language Models for Fine-Grained Renal Pathology
Zhenhao Guo, Rachit Saluja, Tianyuan Yao +14
Fine-grained glomerular subtyping is essential for kidney biopsy interpretation, yet it presents a harder setting than the broad organ- or disease-level recognition tasks commonly…
Glo-VLMs: Leveraging Vision-Language Models for Fine-Grained Diseased Glomerulus Classification
Zhenhao Guo, Rachit Saluja, Tianyuan Yao +8
Vision-language models (VLMs) have shown considerable potential in digital pathology, yet their effectiveness remains limited for fine-grained, disease-specific classification task…
CASC-AI: Consensus-aware Self-corrective Learning for Noise Cell Segmentation
Ruining Deng, Yihe Yang, David J. Pisapia +15
Multi-class cell segmentation in high-resolution gigapixel whole slide images (WSIs) is crucial for various clinical applications. However, training such models typically requires…
Cancer Type, Stage and Prognosis Assessment from Pathology Reports using LLMs
Rachit Saluja, Jacob Rosenthal, Yoav Artzi +3
Large Language Models (LLMs) have shown significant promise across various natural language processing tasks. However, their application in the field of pathology, particularly for…
Characterizing the Features of Mitotic Figures Using a Conditional Diffusion Probabilistic Model
Cagla Deniz Bahadir, Benjamin Liechty, David J. Pisapia +1
Mitotic figure detection in histology images is a hard-to-define, yet clinically significant task, where labels are generated with pathologist interpretations and where there is no…