mlsanityData to 14 Oct 2026

Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction using Patch-based Graph Convolutional Networks

arXiv 2107.13048 ↗First posted 27 Jul 2021eess.IV cs.CV q-bio.TOcited by 124

Not on the map. Why?

Abstract (arXiv)

Cancer prognostication is a challenging task in computational pathology that requires context-aware representations of histology features to adequately infer patient survival. Despite the advancements made in weakly-supervised deep learning, many approaches are not context-aware and are unable to model important morphological feature interactions between cell identities and tissue types that are prognostic for patient survival. In this work, we present Patch-GCN, a context-aware, spatially-resolved patch-based graph convolutional network that hierarchically aggregates instance-level histology features to model local- and global-level topological structures in the tumor microenvironment. We validate Patch-GCN with 4,370 gigapixel WSIs across five different cancer types from the Cancer Genome Atlas (TCGA), and demonstrate that Patch-GCN outperforms all prior weakly-supervised approaches by 3.58-9.46%. Our code and corresponding models are publicly available at https://github.com/mahmoodlab/Patch-GCN.

Key facts. Cited by 124 papers in the map (data through 14 Oct 2026). Builds on 16 of its 40 references that are in the map. First posted on arXiv 27 Jul 2021.

Builds on

16 of 40 references.

References · 16

  1. 2017Deep Setscited by 1,421
  2. 2018Attention-based Deep Multiple Instance Learningcited by 1,095
  3. 2020Data Efficient and Weakly Supervised Computational Pathology on Whole Slide Imagescited by 745
  4. 2019DeepGCNs: Can GCNs Go as Deep as CNNs?cited by 527
  5. 2020Whole Slide Images based Cancer Survival Prediction using Attention Guided Deep Multiple Instance Learning Networkscited by 178
  6. 2019Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosiscited by 165
  7. 2020Deep Learning-based Computational Pathology Predicts Origins for Cancers of Unknown Primarycited by 89
  8. 2019CGC-Net: Cell Graph Convolutional Network for Grading of Colorectal Cancer Histology Imagescited by 57
  9. 2018Deep Adversarial Training for Multi-Organ Nuclei Segmentation in Histopathology Imagescited by 56
  10. 2020Federated Learning for Computational Pathology on Gigapixel Whole Slide Imagescited by 54
  11. 2019Semi-Supervised Histology Classification using Deep Multiple Instance Learning and Contrastive Predictive Codingcited by 35
  12. 2020Quantifying Explainers of Graph Neural Networks in Computational Pathologycited by 35
4 more
  1. 2020Interpretable Survival Prediction for Colorectal Cancer using Deep Learningcited by 30
  2. 2019Histographs: Graphs in Histopathologycited by 20
  3. 2019Weakly Supervised Prostate TMA Classification via Graph Convolutional Networkscited by 17
  4. 2021A digital score of tumour-associated stroma infiltrating lymphocytes predicts survival in head and neck squamous cell carcinomacited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 1; 2022: 9; 2023: 16; 2024: 31; 2025: 38; 2026: 29.

124 papers.

Sort:

By area:

  1. 2023Visual Language Pretrained Multiple Instance Zero-Shot Transfer for Histopathology Imagescited by 134
  2. 2023Artificial Intelligence for Digital and Computational Pathologycited by 108
  3. 2022A graph-transformer for whole slide image classificationcited by 84
  4. 2024Dynamic Graph Representation with Knowledge-aware Attention for Histopathology Whole Slide Image Analysiscited by 67
  5. 2022Self-Supervised Vision Transformers Learn Visual Concepts in Histopathologycited by 50
  6. 2023Histopathology Whole Slide Image Analysis with Heterogeneous Graph Representation Learningcited by 47
  7. 2022AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide Imagescited by 24
  8. 2023AMIGO: Sparse Multi-Modal Graph Transformer with Shared-Context Processing for Representation Learning of Giga-pixel Imagescited by 18
  9. 2023HIGT: Hierarchical Interaction Graph-Transformer for Whole Slide Image Analysiscited by 17
  10. 2024MSCPT: Few-shot Whole Slide Image Classification with Multi-scale and Context-focused Prompt Tuningcited by 16
  11. 2023HVTSurv: Hierarchical Vision Transformer for Patient-Level Survival Prediction from Whole Slide Imagecited by 14
  12. 2024Interpretable Vision-Language Survival Analysis with Ordinal Inductive Bias for Computational Pathologycited by 14
38 more
  1. 2024MamMIL: Multiple Instance Learning for Whole Slide Images with State Space Modelscited by 12
  2. 2024Rethinking Transformer for Long Contextual Histopathology Whole Slide Image Analysiscited by 12
  3. 2022Incorporating intratumoral heterogeneity into weakly-supervised deep learning models via variance poolingcited by 11
  4. 2025Multimodal Cancer Survival Analysis via Hypergraph Learning with Cross-Modality Rebalancecited by 11
  5. 2022DSCA: A Dual-Stream Network with Cross-Attention on Whole-Slide Image Pyramids for Cancer Prognosiscited by 10
  6. 2024Benchmarking Embedding Aggregation Methods in Computational Pathology: A Clinical Data Perspectivecited by 10
  7. 2024Sm: enhanced localization in Multiple Instance Learning for medical imaging classificationcited by 10
  8. 2023MGCT: Mutual-Guided Cross-Modality Transformer for Survival Outcome Prediction using Integrative Histopathology-Genomic Featurescited by 8
  9. 2024SCMIL: Sparse Context-aware Multiple Instance Learning for Predicting Cancer Survival Probability Distribution in Whole Slide Imagescited by 8
  10. 2022Graph Convolutional Networks for Multi-modality Medical Imaging: Methods, Architectures, and Clinical Applicationscited by 7
  11. 2022Kernel Attention Transformer (KAT) for Histopathology Whole Slide Image Classificationcited by 7
  12. 2024SurvMamba: State Space Model with Multi-grained Multi-modal Interaction for Survival Predictioncited by 7
  13. 2024Combining Graph Neural Network and Mamba to Capture Local and Global Tissue Spatial Relationships in Whole Slide Imagescited by 7
  14. 2024GTP-4o: Modality-prompted Heterogeneous Graph Learning for Omni-modal Biomedical Representationcited by 7
  15. 2024From Correlation to Causation: Max-Pooling-Based Multi-Instance Learning Leads to More Robust Whole Slide Image Classificationcited by 7
  16. 2025MiCo: Multiple Instance Learning with Context-Aware Clustering for Whole Slide Image Analysiscited by 7
  17. 2022Multi-Scale Relational Graph Convolutional Network for Multiple Instance Learning in Histopathology Imagescited by 6
  18. 2024Histo-Genomic Knowledge Distillation For Cancer Prognosis From Histopathology Whole Slide Imagescited by 6
  19. 2024Integrative Graph-Transformer Framework for Histopathology Whole Slide Image Representation and Classificationcited by 6
  20. 2024SAM-MIL: A Spatial Contextual Aware Multiple Instance Learning Approach for Whole Slide Image Classificationcited by 6
  21. 2025Self-Supervision Enhances Instance-based Multiple Instance Learning Methods in Digital Pathology: A Benchmark Studycited by 6
  22. 2026ASMIL: Attention-Stabilized Multiple Instance Learning for Whole Slide Imagingcited by 6
  23. 2023Multi-scale Efficient Graph-Transformer for Whole Slide Image Classificationcited by 5
  24. 2024GRASP: GRAph-Structured Pyramidal Whole Slide Image Representationcited by 5
  25. 2024cDP-MIL: Robust Multiple Instance Learning via Cascaded Dirichlet Processcited by 5
  26. 2025Fast and Accurate Gigapixel Pathological Image Classification with Hierarchical Distillation Multi-Instance Learningcited by 5
  27. 2023Context-Aware Self-Supervised Learning of Whole Slide Imagescited by 4
  28. 2024Diagnostic Text-guided Representation Learning in Hierarchical Classification for Pathological Whole Slide Imagecited by 4
  29. 2026Momentum Memory for Knowledge Distillation in Computational Pathologycited by 4
  30. 2021Pan-Cancer Integrative Histology-Genomic Analysis via Interpretable Multimodal Deep Learningcited by 3
  31. 2023AugDiff: Diffusion based Feature Augmentation for Multiple Instance Learning in Whole Slide Imagecited by 3
  32. 2023Long-MIL: Scaling Long Contextual Multiple Instance Learning for Histopathology Whole Slide Image Analysiscited by 3
  33. 2025MGPATH: Vision-Language Model with Multi-Granular Prompt Learning for Few-Shot WSI Classificationcited by 3
  34. 2025PathVQ: Reforming Computational Pathology Foundation Model for Whole Slide Image Analysis via Vector Quantizationcited by 3
  35. 2025PH2ST:ST-Prompt Guided Histological Hypergraph Learning for Spatial Gene Expression Predictioncited by 3
  36. 2025Cracking Instance Jigsaw Puzzles: An Alternative to Multiple Instance Learning for Whole Slide Image Analysiscited by 3
  37. 2025PTCMIL: Multiple Instance Learning via Prompt Token Clustering for Whole Slide Image Analysiscited by 3
  38. 2025PS3: A Multimodal Transformer Integrating Pathology Reports with Histology Images and Biological Pathways for Cancer Survival Predictioncited by 3

50 most cited of 124 All 124 (JSON)