Review of research on the instance segmentation of cell images
- PMID: 36356384
- DOI: 10.1016/j.cmpb.2022.107211
Review of research on the instance segmentation of cell images
Abstract
The instance segmentation of cell images is the basis for conducting cell research and is of great importance for the study and diagnosis of pathologies. To analyze current situations and future developments in the field of cell image instance segmentation, this paper first systematically reviews image segmentation methods based on traditional and deep learning methods. Then, from the three aspects of cell image weak label extraction, cell image instance segmentation, and cell internal structure segmentation, deep-learning-based cell image segmentation methods are analyzed and summarized. Finally, cell image instance segmentation is summarized, and challenges and future developments are discussed.
Keywords: Cell segmentation; Deep learning; Target detection.
Copyright © 2022. Published by Elsevier B.V.
Conflict of interest statement
Declaration of Competing Interest No conflict of interest exits in the submission of this manuscript, and manuscript is approved by all authors for publication. I would like to declare on behalf of my co-authors that the work described was original research that has not been published previously, and not under consideration for publication elsewhere, in whole or in part. All the authors listed have approved the manuscript that is enclosed.
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