469 citations · 706 across the 29 of their papers we have counts for
31 papers
Potential Role of Agentic Artificial Intelligence in Toxicologic Pathology
Nasir Rajpoot, Richard Haworth, Xavier Palazzi +14
As the volume and complexity of nonclinical toxicology studies continue to increase, toxicologic pathology reporting faces persistent challenges, including fragmented sources of da…
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…
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…
StainFuser: Controlling Diffusion for Faster Neural Style Transfer in Multi-Gigapixel Histology Images
Robert Jewsbury, Ruoyu Wang, Abhir Bhalerao +2
Stain normalization algorithms aim to transform the color and intensity characteristics of a source multi-gigapixel histology image to match those of a target image, mitigating inc…
An AI based Digital Score of Tumour-Immune Microenvironment Predicts Benefit to Maintenance Immunotherapy in Advanced Oesophagogastric Adenocarcinoma
Quoc Dang Vu, Caroline Fong, Anderley Gordon +7
Gastric and oesophageal (OG) cancers are the leading causes of cancer mortality worldwide. In OG cancers, recent studies have showed that PDL1 immune checkpoint inhibitors (ICI) in…
TIAViz: A Browser-based Visualization Tool for Computational Pathology Models
Mark Eastwood, John Pocock, Mostafa Jahanifar +8
Digital pathology has gained significant traction in modern healthcare systems. This shift from optical microscopes to digital imagery brings with it the potential for improved dia…
A Fully Automated and Explainable Algorithm for the Prediction of Malignant Transformation in Oral Epithelial Dysplasia
Adam J Shephard, Raja Muhammad Saad Bashir, Hanya Mahmood +11
Oral epithelial dysplasia (OED) is a premalignant histopathological diagnosis given to lesions of the oral cavity. Its grading suffers from significant inter-/intra- observer varia…
Unsupervised Mutual Transformer Learning for Multi-Gigapixel Whole Slide Image Classification
Sajid Javed, Arif Mahmood, Talha Qaiser +2
Classification of gigapixel Whole Slide Images (WSIs) is an important prediction task in the emerging area of computational pathology. There has been a surge of research in deep le…
Synthesis of Annotated Colorectal Cancer Tissue Images from Gland Layout
Srijay Deshpande, Fayyaz Minhas, Nasir Rajpoot
Generating realistic tissue images with annotations is a challenging task that is important in many computational histopathology applications. Synthetically generated images and an…
Why is the winner the best?
Matthias Eisenmann, Annika Reinke, Vivienn Weru +122
International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to in…
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting
Simon Graham, Quoc Dang Vu, Mostafa Jahanifar +86
Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovatio…
Consistency Regularisation in Varying Contexts and Feature Perturbations for Semi-Supervised Semantic Segmentation of Histology Images
Raja Muhammad Saad Bashir, Talha Qaiser, Shan E Ahmed Raza +1
Semantic segmentation of various tissue and nuclei types in histology images is fundamental to many downstream tasks in the area of computational pathology (CPath). In recent years…
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…
Understanding metric-related pitfalls in image analysis validation
Annika Reinke, Minu D. Tizabi, Michael Baumgartner +75
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation int…
Nuclear Segmentation and Classification: On Color & Compression Generalization
Quoc Dang Vu, Robert Jewsbury, Simon Graham +5
Since the introduction of digital and computational pathology as a field, one of the major problems in the clinical application of algorithms has been the struggle to generalize we…
LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset
Yiping Jiao, Jeroen van der Laak, Shadi Albarqouni +18
We introduce LYSTO, the Lymphocyte Assessment Hackathon, which was held in conjunction with the MICCAI 2019 Conference in Shenzen (China). The competition required participants to…
SynCLay: Interactive Synthesis of Histology Images from Bespoke Cellular Layouts
Srijay Deshpande, Muhammad Dawood, Fayyaz Minhas +1
Automated synthesis of histology images has several potential applications in computational pathology. However, no existing method can generate realistic tissue images with a bespo…
An Aggregation of Aggregation Methods in Computational Pathology
Mohsin Bilal, Robert Jewsbury, Ruoyu Wang +4
Image analysis and machine learning algorithms operating on multi-gigapixel whole-slide images (WSIs) often process a large number of tiles (sub-images) and require aggregating pre…
Embedding Space Augmentation for Weakly Supervised Learning in Whole-Slide Images
Imaad Zaffar, Guillaume Jaume, Nasir Rajpoot +1
Multiple Instance Learning (MIL) is a widely employed framework for learning on gigapixel whole-slide images (WSIs) from WSI-level annotations. In most MIL based analytical pipelin…