Adapting Mask-RCNN for Automatic Nucleus Segmentation
arXiv:1805.00500 · doi:10.1007/978-3-030-17798-0
Abstract
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.
arXiv comment7 pages, 3 figures
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