  Automatic segmentation of microscopy images is an important task in medical
image processing and analysis. Nucleus detection is an important example of
this task. Mask-RCNN is a recently proposed state-of-the-art algorithm for
object detection, object localization, and object instance segmentation of
natural images. In this paper we demonstrate that Mask-RCNN can be used to
perform highly effective and efficient automatic segmentations of a wide range
of microscopy images of cell nuclei, for a variety of cells acquired under a
variety of conditions.
