Transformer-based unsupervised contrastive learning for histopathological image classification

2022/07/30 by Xiyue Wang, Sen Yang, Jun Zhang +5 · 1 voice · 8 citations
Computer Science · Medicine · #AI in cancer detection #Colorectal Cancer Screening and Detection #Radiomics and Machine Learning in Medical Imaging

paper · doi:10.1016/j.media.2022.102559

openalex publication_date 2022/07/30 · crossref created 2022/07/30 · crossref issued 2022/10/01 · crossref published 2022/10/01 · crossref published-print 2022/10/01 · openalex created_date 2025/10/10 · crossref deposited 2025/10/23 · crossref indexed 2026/08/04 · openalex updated_date 2026/08/04

Citations

• ImageNet Large Scale Visual Recognition Challenge
• Unsupervised Representation Learning by Predicting Image Rotations
• Improved Baselines with Momentum Contrastive Learning
• Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
• Emerging Properties in Self-Supervised Vision Transformers
• Self-Supervised Learning with Swin Transformers
• CAiD: Context-Aware Instance Discrimination for Self-supervised Learning in Medical Imaging

Cited by

• Understanding Synergistic Interactions among Pathology Foundation Models via Adaptive Fusion
• Multimodal Cancer Survival Analysis via Hypergraph Learning with Cross-Modality Rebalance
• MIPHEI-ViT: Multiplex Immunofluorescence Prediction from H&E Images using ViT Foundation Models
• VIGIL: Vision-Language Guided Multiple Instance Learning Framework for Ulcerative Colitis Histological Healing Prediction
• Enhancing Thyroid Cytology Diagnosis with RAG-Optimized LLMs and Pa-thology Foundation Models
• SimMIL: A Universal Weakly Supervised Pre-Training Framework for Multi-Instance Learning in Whole Slide Pathology Images
• Self-Supervision Enhances Instance-based Multiple Instance Learning Methods in Digital Pathology: A Benchmark Study
• Confounding factors and biases abound when predicting molecular biomarkers from histological images

Discussions

• ... CTransPath (by Wang et al., doi.org/10.1016/j.me...) and additionally, we observed similar results when comparing against the larger UNI model (by Chen et al., doi.org/10.1038/s415..., see the ap [bsky, 0 points, 1 comments]