activity
20242026
collaborators

6 papers

cs.CV2026

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…

cs.CV2026

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)…

cs.CV2025

DiA-gnostic VLVAE: Disentangled Alignment-Constrained Vision Language Variational AutoEncoder for Robust Radiology Reporting with Missing Modalities

Nagur Shareef Shaik, Teja Krishna Cherukuri, Adnan Masood +1

The integration of medical images with clinical context is essential for generating accurate and clinically interpretable radiology reports. However, current automated methods ofte…

eess.IV2025

Ordinal Label-Distribution Learning with Constrained Asymmetric Priors for Imbalanced Retinal Grading

Nagur Shareef Shaik, Teja Krishna Cherukuri, Adnan Masood +2

Diabetic retinopathy grading is inherently ordinal and long-tailed, with minority stages being scarce, heterogeneous, and clinically critical to detect accurately. Conventional met…

cs.CV2025

Dynamic Contextual Attention Network: Transforming Spatial Representations into Adaptive Insights for Endoscopic Polyp Diagnosis

Teja Krishna Cherukuri, Nagur Shareef Shaik, Sribhuvan Reddy Yellu +2

Colorectal polyps are key indicators for early detection of colorectal cancer. However, traditional endoscopic imaging often struggles with accurate polyp localization and lacks co…

cs.CV2024

GCS-M3VLT: Guided Context Self-Attention based Multi-modal Medical Vision Language Transformer for Retinal Image Captioning

Teja Krishna Cherukuri, Nagur Shareef Shaik, Jyostna Devi Bodapati +1

Retinal image analysis is crucial for diagnosing and treating eye diseases, yet generating accurate medical reports from images remains challenging due to variability in image qual…