Iterative unsupervised domain adaptation for generalized cell detection from brightfield z-stacks.
Journal:
BMC bioinformatics
Published Date:
Feb 15, 2019
Abstract
BACKGROUND: Cell counting from cell cultures is required in multiple biological and biomedical research applications. Especially, accurate brightfield-based cell counting methods are needed for cell growth analysis. With deep learning, cells can be detected with high accuracy, but manually annotated training data is required. We propose a method for cell detection that requires annotated training data for one cell line only, and generalizes to other, unseen cell lines.