mlsanityData to 14 Oct 2026

WISE: A Framework for Gigapixel Whole-Slide-Image Lossless Compression

arXiv 2503.18074 ↗First posted 23 Mar 2025eess.IV cs.CVcited by 3

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Abstract (arXiv)

Whole-Slide Images (WSIs) have revolutionized medical analysis by presenting high-resolution images of the whole tissue slide. Despite avoiding the physical storage of the slides, WSIs require considerable data volume, which makes the storage and maintenance of WSI records costly and unsustainable. To this end, this work presents the first investigation of lossless compression of WSI images. Interestingly, we find that most existing compression methods fail to compress the WSI images effectively. Furthermore, our analysis reveals that the failure of existing compressors is mainly due to information irregularity in WSI images. To resolve this issue, we developed a simple yet effective lossless compressor called WISE, specifically designed for WSI images. WISE employs a hierarchical encoding strategy to extract effective bits, reducing the entropy of the image and then adopting a dictionary-based method to handle the irregular frequency patterns. Through extensive experiments, we show that WISE can effectively compress the gigapixel WSI images to 36 times on average and up to 136 times.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 16 of its 37 references that are in the map. First posted on arXiv 23 Mar 2025.

Builds on

16 of 37 references.

References · 16

  1. 2016Pixel Recurrent Neural Networkscited by 816
  2. 2017PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modificationscited by 417
  3. 2019Integer Discrete Flows and Lossless Compressioncited by 83
  4. 2019Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variablescited by 52
  5. 2023Histopathology Whole Slide Image Analysis with Heterogeneous Graph Representation Learningcited by 47
  6. 2021Predicting Axillary Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Primary Tumor Biopsy Slidescited by 43
  7. 2020IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compressioncited by 36
  8. 2022A Fast Transformer-based General-Purpose Lossless Compressorcited by 26
  9. 2023Predicting Ki67, ER, PR, and HER2 Statuses from H&E-stained Breast Cancer Imagescited by 14
  10. 2020Extending Unsupervised Neural Image Compression With Supervised Multitask Learningcited by 12
  11. 2021LC-FDNet: Learned Lossless Image Compression with Frequency Decomposition Networkcited by 12
  12. 2024Advances in Multiple Instance Learning for Whole Slide Image Analysis: Techniques, Challenges, and Future Directionscited by 7
4 more
  1. 2020Geometrically Matched Multi-source Microscopic Image Synthesis Using Bidirectional Adversarial Networkscited by 5
  2. 2024DiffKillR: Killing and Recreating Diffeomorphisms for Cell Annotation in Dense Microscopy Imagescited by 5
  3. 2024SHAP-CAT: A interpretable multi-modal framework enhancing WSI classification via virtual staining and shapley-value-based multimodal fusioncited by 3
  4. 2023A Deep Learning-based Compression and Classification Technique for Whole Slide Histopathology Imagescited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.

  1. 2025Joint Lossless Compression and Steganography for Medical Images via Large Language Modelscited by 6
  2. 2026Multimodal Model for Computational Pathology:Representation Learning and Image Compressioncited by 6
  3. 2025MVHybrid: Improving Spatial Transcriptomics Prediction with Hybrid State Space-Vision Transformer Backbone in Pathology Vision Foundation Modelscited by 1