mlsanityData to 7 Oct 2026

Deep Multi-Magnification Networks for Multi-Class Breast Cancer Image Segmentation

arXiv 1910.13042 ↗First posted 29 Oct 2019eess.IV cs.CVcited by 22

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Abstract (arXiv)

Pathologic analysis of surgical excision specimens for breast carcinoma is important to evaluate the completeness of surgical excision and has implications for future treatment. This analysis is performed manually by pathologists reviewing histologic slides prepared from formalin-fixed tissue. In this paper, we present Deep Multi-Magnification Network trained by partial annotation for automated multi-class tissue segmentation by a set of patches from multiple magnifications in digitized whole slide images. Our proposed architecture with multi-encoder, multi-decoder, and multi-concatenation outperforms other single and multi-magnification-based architectures by achieving the highest mean intersection-over-union, and can be used to facilitate pathologists' assessments of breast cancer.

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Oct 2019.

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Citing papers per year: 2021: 2; 2022: 8; 2023: 7; 2024: 3; 2025: 1; 2026: 1.

22 papers.

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  1. 2022Differentiable Zooming for Multiple Instance Learning on Whole-Slide Imagescited by 43
  2. 2023OCELOT: Overlapped Cell on Tissue Dataset for Histopathologycited by 29
  3. 2021Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphscited by 22
  4. 2023Weakly Supervised Joint Whole-Slide Segmentation and Classification in Prostate Cancercited by 10
  5. 2023Deep Learning in Breast Cancer Imaging: A Decade of Progress and Future Directionscited by 10
  6. 2022Efficient High-Resolution Deep Learning: A Surveycited by 9
  7. 2022H&E-based Computational Biomarker Enables Universal EGFR Screening for Lung Adenocarcinomacited by 8
  8. 2023DPA-P2PNet: Deformable Proposal-aware P2PNet for Accurate Point-based Cell Detectioncited by 8
  9. 2022Deep Interactive Learning-based ovarian cancer segmentation of H&E-stained whole slide images to study morphological patterns of BRCA mutationcited by 7
  10. 2021A QuadTree Image Representation for Computational Pathologycited by 4
  11. 2022Stain-invariant self supervised learning for histopathology image analysiscited by 4
  12. 2022A review of machine learning approaches, challenges and prospects for computational tumor pathologycited by 3
10 more
  1. 2022Deep Multi-Scale U-Net Architecture and Label-Noise Robust Training Strategies for Histopathological Image Segmentationcited by 2
  2. 2023Partial Vessels Annotation-based Coronary Artery Segmentation with Self-training and Prototype Learningcited by 2
  3. 2022Deep Learning-Based Objective and Reproducible Osteosarcoma Chemotherapy Response Assessment and Outcome Predictioncited by 1
  4. 2024Segmentation, Classification and Interpretation of Breast Cancer Medical Images using Human-in-the-Loop Machine Learningcited by 1
  5. 2023Robust Tumor Detection from Coarse Annotations via Multi-Magnification Ensemblescited by 0
  6. 2023The State of Applying Artificial Intelligence to Tissue Imaging for Cancer Research and Early Detectioncited by 0
  7. 2024Multi-Stain Multi-Level Convolutional Network for Multi-Tissue Breast Cancer Image Segmentationcited by 0
  8. 2024Segmentation of Non-Small Cell Lung Carcinomas: Introducing DRU-Net and Multi-Lens Distortioncited by 0
  9. 2025GNCAF: A GNN-based Neighboring Context Aggregation Framework for Tertiary Lymphoid Structures Semantic Segmentation in WSIcited by 0
  10. 2026Adapting Vision Transformers to Ultra-High Resolution Semantic Segmentation with Relay Tokenscited by 0