14 papers
Inference-Time Orthogonal Seeding Enables Geometry-Aligned 3D Organ Segmentation for Slice-Propagation Methods
Md Rakibul Haque, Tushar Kataria, Shireen Y. Elhabian
Dense voxel-level annotation remains a major bottleneck in 3D medical image segmentation. Single-slice propagation methods such as Sli2Vol reduce this burden by propagating one ann…
MedConcept: Unsupervised Concept Discovery for Interpretability in Medical VLMs
Md Rakibul Haque, KM Arefeen Sultan, Tushar Kataria +1
While medical Vision-Language models (VLMs) achieve strong performance on tasks such as tumor or organ segmentation and diagnosis prediction, their opaque latent representations li…
MorphoFlow: Sparse-Supervised Generative Shape Modeling with Adaptive Latent Relevance
Mokshagna Sai Teja Karanam, Tushar Kataria, Shireen Elhabian
Statistical shape modeling (SSM) is central to population level analysis of anatomical variability, yet most existing approaches rely on densely annotated segmentations and fixed l…
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…
MapVerse: A Benchmark for Geospatial Question Answering on Diverse Real-World Maps
Sharat Bhat, Harshita Khandelwal, Tushar Kataria +1
Maps are powerful carriers of structured and contextual knowledge, encompassing geography, demographics, infrastructure, and environmental patterns. Reasoning over such knowledge r…
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.…