469 citations · 706 across the 29 of their papers we have counts for
6 papers · 1 filter
MPath: Multimodal Pathology Report Generation from Whole Slide Images
Noorul Wahab, Nasir Rajpoot
Automated generation of diagnostic pathology reports directly from whole slide images (WSIs) is an emerging direction in computational pathology. Translating high-resolution tissue…
Tissue Aware Nuclei Detection and Classification Model for Histopathology Images
Kesi Xu, Eleni Chiou, Ali Varamesh +2
Accurate nuclei detection and classification are fundamental to computational pathology, yet existing approaches are hindered by reliance on detailed expert annotations and insuffi…
A Deep Learning Framework for Thyroid Nodule Segmentation and Malignancy Classification from Ultrasound Images
Omar Abdelrazik, Mohamed Elsayed, Noorul Wahab +2
Ultrasound-based risk stratification of thyroid nodules is a critical clinical task, but it suffers from high inter-observer variability. While many deep learning (DL) models funct…
Synergy vs. Noise: Performance-Guided Multimodal Fusion For Biochemical Recurrence-Free Survival in Prostate Cancer
Seth Alain Chang, Muhammad Mueez Amjad, Noorul Wahab +3
Multimodal deep learning (MDL) has emerged as a transformative approach in computational pathology. By integrating complementary information from multiple data sources, MDL models…
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…
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…