Using simulated fluorescence cell micrographs for the evaluation of cell image segmentation algorithms.

Veit WiesmannMatthias BerglerRalf PalmisanoMartin PrinzenDaniela FranzThomas Wittenberg

Published in: BMC bioinformatics (2017)

The proposed simulation approach produces realistic fluorescent cell micrographs with corresponding ground truth. The simulated data is suited to evaluate image segmentation pipelines more efficiently and reproducibly than it is possible on manually annotated real micrographs.

Keyphrases

deep learning
single cell
cell therapy
machine learning
convolutional neural network
stem cells
electronic health record