mlsanityData to 7 Oct 2026

Multi-Resolution Networks for Semantic Segmentation in Whole Slide Images

arXiv 1807.09607 ↗First posted 25 Jul 2018cs.CVcited by 14

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Abstract (arXiv)

Digital pathology provides an excellent opportunity for applying fully convolutional networks (FCNs) to tasks, such as semantic segmentation of whole slide images (WSIs). However, standard FCNs face challenges with respect to multi-resolution, inherited from the pyramid arrangement of WSIs. As a result, networks specifically designed to learn and aggregate information at different levels are desired. In this paper, we propose two novel multi-resolution networks based on the popular `U-Net' architecture, which are evaluated on a benchmark dataset for binary semantic segmentation in WSIs. The proposed methods outperform the U-Net, demonstrating superior learning and generalization capabilities.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Jul 2018.

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

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  1. 2022A Morphology Focused Diffusion Probabilistic Model for Synthesis of Histopathology Imagescited by 74
  2. 2021Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slidescited by 43
  3. 2022Towards Label-efficient Automatic Diagnosis and Analysis: A Comprehensive Survey of Advanced Deep Learning-based Weakly-supervised, Semi-supervised and Self-supervised Techniques in Histopathological Image Analysiscited by 29
  4. 2021FastSurferVINN: Building Resolution-Independence into Deep Learning Segmentation Methods -- A Solution for HighRes Brain MRIcited by 18
  5. 2024WSI-SAM: Multi-resolution Segment Anything Model (SAM) for histopathology whole-slide imagescited by 7
  6. 2023A Dual-branch Self-supervised Representation Learning Framework for Tumour Segmentation in Whole Slide Imagescited by 5
  7. 2022Valuing Vicinity: Memory attention framework for context-based semantic segmentation in histopathologycited by 3
  8. 2023Improved distinct bone segmentation in upper-body CT through multi-resolution networkscited by 2
  9. 2026AtlasPatch: Scalable Foundation Model-based Tissue Detection and Patch Extraction for Computational Pathologycited by 1
  10. 2024Multi-Stain Multi-Level Convolutional Network for Multi-Tissue Breast Cancer Image Segmentationcited by 0
  11. 2024Distilling High Diagnostic Value Patches for Whole Slide Image Classification Using Attention Mechanismcited by 0
  12. 2025TUMLS: Trustful Fully Unsupervised Multi-Level Segmentation for Whole Slide Images of Histologycited by 0
2 more
  1. 2025GNCAF: A GNN-based Neighboring Context Aggregation Framework for Tertiary Lymphoid Structures Semantic Segmentation in WSIcited by 0
  2. 2026Adapting Vision Transformers to Ultra-High Resolution Semantic Segmentation with Relay Tokenscited by 0