TIGER is the first challenge on fully automated assessment of tumor-infiltrating lymphocytes (TILs) in H&E breast cancer slides. The goal of this challenge is to evaluate new computer algorithms for the automated assessment of tumor-infiltrating lymphocytes (TILs) in Her2 positive and Triple Negative breast cancer (BC) histopathology slides. In recent years, several studies have shown the predictive and prognostic value of visually scored TILs in BC as well as in other cancer types, making TILs a powerful biomarker that can potentially be used in the clinic. With TIGER, we aim at developing computer algorithms that can automatically generate a "TIL score" with a high prognostic value.
Participants in the TIGER challenge will have to develop computer algorithms to analyze H&E-stained whole-slide images of breast cancer histopathology, to perform three tasks:
- detection of lymphocytes and plasma cells, which are the main types of cells considered as tumor-infiltrating lymphocytes;
- segmentation of invasive tumor and tumor-associated stroma, which are the main tissue compartments considered when identifying relevant regions for the TILs;
- compute an automated TILs score, one score per slide, based on the output of detection and segmentation.
Participate in the challenge
The TIGER challenge is supported by