Analysis of the performance of U-Net neural networks for the segmentation of living cells. (arXiv:2210.01538v1 [q-bio.QM])

The automated analysis of microscopy images is a challenge in the context of
single-cell tracking and quantification. This work has as goals the study of
the performance of deep learning for segmenting microscopy images and the
improvement of the previously available pipeline for tracking single cells.
Deep learning techniques, mainly convolutional neural networks, have been
applied to cell segmentation problems and have shown high accuracy and fast
performance. To perform the image segmentation, an analysis of hyperparameters
was done in …

analysis arxiv bio cells networks neural networks performance segmentation