2 citations · 7 across the 21 of their papers we have counts for
5 papers · 1 filter
Building Trust in Virtual Immunohistochemistry: Automated Assessment of Image Quality
Tushar Kataria, Shikha Dubey, Mary Bronner +4
Deep learning models can generate virtual immunohistochemistry (IHC) stains from hematoxylin and eosin (H&E) images, offering a scalable and low-cost alternative to laboratory IHC.…
IMPLICITSTAINER: Resolution Agnostic Data-Efficient Virtual Staining Using Neural Implicit Functions
Tushar Kataria, Beatrice Knudsen, Shireen Y. Elhabian
Hematoxylin and eosin (H&E)-stained slides are central to cancer diagnosis and monitoring, visualizing tissue architecture and cellular morphology. However, H&E lacks the molecular…
BoundarySeg:Boundary-Aware Multi-Task Learning for Semi-Supervised 3D Medical Image Segmentation with Limited Unlabeled Data
Tushar Kataria, Shireen Y. Elhabian
Data scarcity is a primary bottleneck in 3D medical image segmentation: expert voxel-level annotations are expensive, and privacy regulations often severely restrict access to unan…
Leveraging LLM For Synchronizing Information Across Multilingual Tables
Siddharth Khincha, Tushar Kataria, Ankita Anand +2
The vast amount of online information today poses challenges for non-English speakers, as much of it is concentrated in high-resource languages such as English and French. Wikipedi…
TransientTables: Evaluating LLMs' Reasoning on Temporally Evolving Semi-structured Tables
Abhilash Shankarampeta, Harsh Mahajan, Tushar Kataria +2
Humans continuously make new discoveries, and understanding temporal sequence of events leading to these breakthroughs is essential for advancing science and society. This ability…