Author

Dwarikanath Mahapatra

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Open access Sep 2026

INFORMER-Interpretability-Founded Monitoring of Medical Image Deep Learning Models: Application to Chest X-ray Pathologies.

Deep learning has demonstrated strong performance in medical imaging. However, its limited interpretability remains a major barrier to clinical trust and safe deployment. This limitation is particularly relevant in multi-label classification, where quality control methods are still underdeveloped and commonly rely only...

Shelley Zixin Shu, Aurélie Pahud de Mortanges, A. Poellinger et al. · Journal of imaging informati... · 0 citations

Preprint Aug 2026

From Multi-Resolution Cells to Gigapixel Whole Slide Images Foundation Model for Computational Pathology

Multi-Resolution Pyramid Transformer (MRPT) is introduced, a model that hierarchically aggregates multi-resolution information from cellular to tissue and WSI levels and surpasses recent foundation models and Multimodal Large Language Models in cancer subtype classification, tissue phenotyping, and Visual Question Answ...

B. Alawode, Moshira Abdalla, Dwarikanath Mahapatra et al. · 0 citations

Preprint Jul 2026

Can Experts Adapt Without Training? On Test-Time Modality Generalization in MVLMs

Medical vision-language models (MVLMs) promise broad zero-shot generalization, yet their reliability collapses when confronted with unseen modalities and domains, precisely where clinical robustness matters most. To address this gap, we revisit test-time modality generalization from the perspective of Mixture-of-Expert...

Raza Imam, Darakshan Rashid, Yutong Xie et al. · 0 citations