Deep Learning-based mitosis detection in breast cancer histologic samples
Michel Halmes, Hippolyte Heuberger, Sylvain Berlemont · arXiv (Cornell University) · 2021
This is the submission for mitosis detection in the context of the MIDOG 2021 challenge. It is based on the two-stage objection model Faster RCNN as well as DenseNet as a backbone for the neural network architecture. It achieves a F1-score of 0.6645 on the Preliminary Test Phase Leaderboard.