A foundation model for clinical-grade computational pathology and rare cancers detection

E Vorontsov, A Bozkurt, A Casson, G Shaikovski… - Nature medicine, 2024 - nature.com
The analysis of histopathology images with artificial intelligence aims to enable clinical
decision support systems and precision medicine. The success of such applications …

Towards a general-purpose foundation model for computational pathology

RJ Chen, T Ding, MY Lu, DFK Williamson, G Jaume… - Nature Medicine, 2024 - nature.com
Quantitative evaluation of tissue images is crucial for computational pathology (CPath) tasks,
requiring the objective characterization of histopathological entities from whole-slide images …

Machine learning in computational histopathology: Challenges and opportunities

M Cooper, Z Ji, RG Krishnan - Genes, Chromosomes and …, 2023 - Wiley Online Library
Digital histopathological images, high‐resolution images of stained tissue samples, are a
vital tool for clinicians to diagnose and stage cancers. The visual analysis of patient state …

Virchow: A million-slide digital pathology foundation model

E Vorontsov, A Bozkurt, A Casson, G Shaikovski… - ar** self-supervised learning (SSL) models that can learn universal and transferable
representations of H&E gigapixel whole-slide images (WSIs) is becoming increasingly …

Morphological prototy** for unsupervised slide representation learning in computational pathology

AH Song, RJ Chen, T Ding… - Proceedings of the …, 2024 - openaccess.thecvf.com
Abstract Representation learning of pathology whole-slide images (WSIs) has been has
primarily relied on weak supervision with Multiple Instance Learning (MIL). However the …

Hest-1k: A dataset for spatial transcriptomics and histology image analysis

G Jaume, P Doucet, AH Song, MY Lu… - arxiv preprint arxiv …, 2024 - arxiv.org
Spatial transcriptomics enables interrogating the molecular composition of tissue with ever-
increasing resolution and sensitivity. However, costs, rapidly evolving technology, and lack …