mlsanityData to 7 Oct 2026

TIAger: Tumor-Infiltrating Lymphocyte Scoring in Breast Cancer for the TiGER Challenge

arXiv 2206.11943 ↗First posted 23 Jun 2022eess.IV cs.CVcited by 7

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Abstract (arXiv)

The quantification of tumor-infiltrating lymphocytes (TILs) has been shown to be an independent predictor for prognosis of breast cancer patients. Typically, pathologists give an estimate of the proportion of the stromal region that contains TILs to obtain a TILs score. The Tumor InfiltratinG lymphocytes in breast cancER (TiGER) challenge, aims to assess the prognostic significance of computer-generated TILs scores for predicting survival as part of a Cox proportional hazards model. For this challenge, as the TIAger team, we have developed an algorithm to first segment tumor vs. stroma, before localising the tumor bulk region for TILs detection. Finally, we use these outputs to generate a TILs score for each case. On preliminary testing, our approach achieved a tumor-stroma weighted Dice score of 0.791 and a FROC score of 0.572 for lymphocytic detection. For predicting survival, our model achieved a C-index of 0.719. These results achieved first place across the preliminary testing leaderboards of the TiGER challenge.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 8 of its 12 references that are in the map. First posted on arXiv 23 Jun 2022.

Builds on

8 of 12 references.

References · 8

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  5. 2021Stain-Robust Mitotic Figure Detection for the Mitosis Domain Generalization Challengecited by 14
  6. 2021Robust Interactive Semantic Segmentation of Pathology Images with Minimal User Inputcited by 8
  7. 2021Simultaneous Nuclear Instance and Layer Segmentation in Oral Epithelial Dysplasiacited by 8
  8. 2018Segmentation of Skin Lesions and their Attributes Using Multi-Scale Convolutional Neural Networks and Domain Specific Augmentationscited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 1; 2025: 3; 2026: 2.

7 papers.