  We propose a two-step domain shift-invariant mitosis cell detection method
based on Faster RCNN and a convolutional neural network (CNN). We generate
various domain-shifted versions of existing histopathology images using a stain
augmentation technique, enabling our method to effectively learn various stain
domains and achieve better generalization. The performance of our method is
evaluated on the preliminary test data set of the MIDOG-2021 challenge. The
experimental results demonstrate that the proposed mitosis detection method can
achieve promising performance for domain-shifted histopathology images.
