5 citations · 12 across the 11 of their papers we have counts for
4 papers · 1 filter
CA: Coupling Spatial Evidence with Clinical Priors via Co-occurrence Aware Class Attention for Multi-Label Chest X-Ray Classification
Akash Gogineni, Nagur Shareef Shaik, Aasrith Mandava +2
Thoracic pathologies rarely occur in isolation, yet standard multi-label classifiers rely on shared global descriptors, discarding \emph{where} findings lie and \emph{how} they co-…
Disentangling Co-Occurring Retinal Pathologies with Saliency-Guided Sparse Expert Routing
Nagur Shareef Shaik, Jeongwoo Park, Yeong-Jin Kim +3
Retinal fundus images frequently exhibit multiple co-occurring pathologies, yet standard deep learning classifiers apply static, identical computation to every image regardless of…
Region-Affinity Attention for Whole-Slide Breast Cancer Classification in Deep Ultraviolet Imaging
Nagur Shareef Shaik, Teja Krishna Cherukuri, Dong Hye Ye
Breast cancer diagnosis demands rapid and precise tools, yet traditional histopathological methods often fall short in intra-operative settings. Deep Ultraviolet (DUV) fluorescence…
DREAM: Dynamic Retinal Enhancement with Adaptive Multi-modal Fusion for Expert Precision Medical Report Generation
Nagur Shareef Shaik, Teja Krishna Cherukuri, Dong Hye Ye
Automating medical reports for retinal images requires a sophisticated blend of visual pattern recognition and deep clinical knowledge. Current Large Vision-Language Models (LVLMs)…