8 papers
Autonomous labeling of surgical resection margins using a foundation model
Xilin Yang, Musa Aydin, Yuhong Lu +9
Assessing resection margins is central to pathological specimen evaluation and has profound implications for patient outcomes. Current practice employs physical inking, which is ap…
Universal and Transferable Attacks on Pathology Foundation Models
Yuntian Wang, Xilin Yang, Che-Yung Shen +2
We introduce Universal and Transferable Adversarial Perturbations (UTAP) for pathology foundation models that reveal critical vulnerabilities in their capabilities. Optimized using…
Deep learning-enabled virtual multiplexed immunostaining of label-free tissue for vascular invasion assessment
Yijie Zhang, Cagatay Isil, Xilin Yang +6
Immunohistochemistry (IHC) has transformed clinical pathology by enabling the visualization of specific proteins within tissue sections. However, traditional IHC requires one tissu…
BlurryScope enables compact, cost-effective scanning microscopy for HER2 scoring using deep learning on blurry images
Michael John Fanous, Christopher Michael Seybold, Hanlong Chen +2
We developed a rapid scanning optical microscope, termed "BlurryScope", that leverages continuous image acquisition and deep learning to provide a cost-effective and compact soluti…
Label-free evaluation of lung and heart transplant biopsies using tissue autofluorescence-based virtual staining
Yuzhu Li, Nir Pillar, Tairan Liu +12
Organ transplantation serves as the primary therapeutic strategy for end-stage organ failures. However, allograft rejection is a common complication of organ transplantation. Histo…
Pixel super-resolved virtual staining of label-free tissue using diffusion models
Yijie Zhang, Luzhe Huang, Nir Pillar +3
Virtual staining of tissue offers a powerful tool for transforming label-free microscopy images of unstained tissue into equivalents of histochemically stained samples. This study…