mlsanityData to 14 Oct 2026

Learning from Partial Label Proportions for Whole Slide Image Segmentation

arXiv 2405.09041 ↗First posted 15 May 2024cs.CVcited by 6

Not on the map. Why?

Abstract (arXiv)

In this paper, we address the segmentation of tumor subtypes in whole slide images (WSI) by utilizing incomplete label proportions. Specifically, we utilize `partial' label proportions, which give the proportions among tumor subtypes but do not give the proportion between tumor and non-tumor. Partial label proportions are recorded as the standard diagnostic information by pathologists, and we, therefore, want to use them for realizing the segmentation model that can classify each WSI patch into one of the tumor subtypes or non-tumor. We call this problem ``learning from partial label proportions (LPLP)'' and formulate the problem as a weakly supervised learning problem. Then, we propose an efficient algorithm for this challenging problem by decomposing it into two weakly supervised learning subproblems: multiple instance learning (MIL) and learning from label proportions (LLP). These subproblems are optimized efficiently in the end-to-end manner. The effectiveness of our algorithm is demonstrated through experiments conducted on two WSI datasets.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 14 of its 27 references that are in the map. First posted on arXiv 15 May 2024.

Builds on

14 of 27 references.

References · 14

  1. 2021TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classificationcited by 555
  2. 2020Dual-stream Multiple Instance Learning Network for Whole Slide Image Classification with Self-supervised Contrastive Learningcited by 478
  3. 2016Revisiting Multiple Instance Neural Networkscited by 119
  4. 2020Multi-scale Domain-adversarial Multiple-instance CNN for Cancer Subtype Classification with Unannotated Histopathological Imagescited by 81
  5. 2022Additive MIL: Intrinsically Interpretable Multiple Instance Learning for Pathologycited by 58
  6. 2022Bi-directional Weakly Supervised Knowledge Distillation for Whole Slide Image Classificationcited by 43
  7. 2019Learning from Label Proportions with Consistency Regularizationcited by 34
  8. 2019Deep multi-class learning from label proportionscited by 33
  9. 2017Co-training for Demographic Classification Using Deep Learning from Label Proportionscited by 28
  10. 2019Learning from Label Proportions with Generative Adversarial Networkscited by 25
  11. 2021Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphscited by 22
  12. 2023Learning from Label Proportion with Online Pseudo-Label Decision by Regret Minimizationcited by 9
2 more
  1. 2023MixBag: Bag-Level Data Augmentation for Learning from Label Proportionscited by 8
  2. 2024Proportion Estimation by Masked Learning from Label Proportioncited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 3; 2026: 2.

6 papers.

  1. 2024Theoretical Proportion Label Perturbation for Learning from Label Proportions in Large Bagscited by 2
  2. 2025Weakly-Supervised Domain Adaptation with Proportion-Constrained Pseudo-Labelingcited by 2
  3. 2025Learning from Similarity Proportion Loss for Classifying Skeletal Muscle Recovery Stagescited by 0
  4. 2025Investigating ECG Diagnosis with Ambiguous Labels using Partial Label Learningcited by 0
  5. 2026Leveraging Label Proportion Prior for Class-Imbalanced Semi-Supervised Learningcited by 0
  6. 2026Semantic Segmentation for Histopathology using Learned Regularization based on Global Proportionscited by 0