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Deep Learning-based mitosis detection in breast cancer histologic samples

arXiv 2109.00816 ↗First posted 2 Sep 2021cs.CV cs.LGcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 4 references that are in the map. First posted on arXiv 2 Sep 2021.

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2 of 4 references.

References · 2

  1. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,639
  2. 2016Densely Connected Convolutional Networkscited by 6,720

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