1 citations · 1 across the 1 of their papers we have counts for
5 papers
Projection Guided Personalized Federated Learning for Low Dose CT Denoising
Anas Zafar, Muhammad Waqas, Amgad Muneer +2
Low-dose CT (LDCT) reduces radiation exposure but introduces protocol-dependent noise and artifacts that vary across institutions. While federated learning enables collaborative tr…
CARL-CXR: Continual Adapter-Based Routing for Task-Unknown Chest Radiograph Classification
Muthu Subash Kavitha, Anas Zafar, Amgad Muneer +1
Clinical deployment of chest radiograph classifiers requires models that can be updated as new datasets become available without retraining on previously observed data or degrading…
Can We Go Beyond Visual Features? Neural Tissue Relation Modeling for Relational Graph Analysis in Non-Melanoma Skin Histology
Shravan Venkatraman, Muthu Subash Kavitha, Joe Dhanith P R +2
Histopathology image segmentation is essential for delineating tissue structures in skin cancer diagnostics, but modeling spatial context and inter-tissue relationships remains a c…
The Next Layer: Augmenting Foundation Models with Structure-Preserving and Attention-Guided Learning for Local Patches to Global Context Awareness in Computational Pathology
Muhammad Waqas, Rukhmini Bandyopadhyay, Eman Showkatian +12
Foundation models have recently emerged as powerful feature extractors in computational pathology, yet they typically omit mechanisms for leveraging the global spatial structure of…
From Classical Machine Learning to Emerging Foundation Models: Review on Multimodal Data Integration for Cancer Research
Amgad Muneer, Muhammad Waqas, Maliazurina B Saad +16
Cancer research is increasingly driven by the integration of diverse data modalities, spanning from genomics and proteomics to imaging and clinical factors. However, extracting act…