20 citations · 38 across the 7 of their papers we have counts for
4 papers · 1 filter
Foundation Models in Biomedical Imaging: Turning Hype into Reality
Amgad Muneer, Kai Zhang, Ibraheem Hamdi +6
Foundation models (FMs) are driving a prominent shift in biomedical imaging from task-specific models to unified backbone models for diverse tasks. This opens an avenue to integrat…
MorphGen: Morphology-Guided Representation Learning for Robust Single-Domain Generalization in Histopathological Cancer Classification
Hikmat Khan, Syed Farhan Alam Zaidi, Pir Masoom Shah +4
Domain generalization in computational histopathology is hindered by heterogeneity in whole slide images (WSIs), caused by variations in tissue preparation, staining, and imaging 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…