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Adapting Mask-RCNN for Automatic Nucleus Segmentation
- Source :
- Proceedings of the 2019 Computer Vision Conference, Vol. 2
- Publication Year :
- 2018
-
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.<br />Comment: 7 pages, 3 figures
Details
- Database :
- arXiv
- Journal :
- Proceedings of the 2019 Computer Vision Conference, Vol. 2
- Publication Type :
- Report
- Accession number :
- edsarx.1805.00500
- Document Type :
- Working Paper
- Full Text :
- https://doi.org/10.1007/978-3-030-17798-0