10 citations · 19 across the 7 of their papers we have counts for
7 papers
PS3: A Multimodal Transformer Integrating Pathology Reports with Histology Images and Biological Pathways for Cancer Survival Prediction
Manahil Raza, Ayesha Azam, Talha Qaiser +1
Current multimodal fusion approaches in computational oncology primarily focus on integrating multi-gigapixel histology whole slide images (WSIs) with genomic or transcriptomic dat…
A Novel Approach to Linking Histology Images with DNA Methylation
Manahil Raza, Muhammad Dawood, Talha Qaiser +1
DNA methylation is an epigenetic mechanism that regulates gene expression by adding methyl groups to DNA. Abnormal methylation patterns can disrupt gene expression and have been li…
Foundation Models in Computational Pathology: A Review of Challenges, Opportunities, and Impact
Mohsin Bilal, Aadam, Manahil Raza +6
From self-supervised, vision-only models to contrastive visual-language frameworks, computational pathology has rapidly evolved in recent years. Generative AI "co-pilots" now demon…
Stain-Invariant Representation for Tissue Classification in Histology Images
Manahil Raza, Saad Bashir, Talha Qaiser +1
The process of digitising histology slides involves multiple factors that can affect a whole slide image's (WSI) final appearance, including the staining protocol, scanner, and tis…
Domain Generalization in Computational Pathology: Survey and Guidelines
Mostafa Jahanifar, Manahil Raza, Kesi Xu +8
Deep learning models have exhibited exceptional effectiveness in Computational Pathology (CPath) by tackling intricate tasks across an array of histology image analysis application…
Dual Attention Model with Reinforcement Learning for Classification of Histology Whole-Slide Images
Manahil Raza, Ruqayya Awan, Raja Muhammad Saad Bashir +2
Digital whole slide images (WSIs) are generally captured at microscopic resolution and encompass extensive spatial data. Directly feeding these images to deep learning models is co…
Cellular Segmentation and Composition in Routine Histology Images using Deep Learning
Muhammad Dawood, Raja Muhammad Saad Bashir, Srijay Deshpande +2
Identification and quantification of nuclei in colorectal cancer haematoxylin \& eosin (H\&E) stained histology images is crucial to prognosis and patient management. In computatio…