Biologically constrained optimization based cell membrane segmentation in C. elegans embryos.

Published in: BMC bioinformatics (2017)

BCOMS automated the accurate extraction of cell shapes in developing C. elegans embryos. By replacing image processing parameters with easily adjustable biological constraints, BCOMS provides a user-friendly framework. The framework is also applicable to other model organisms. Creating the biological constraints is a critical step requiring collaboration between an experimentalist and a software developer.

Keyphrases

deep learning
convolutional neural network
single cell
machine learning
cell therapy
high throughput
high resolution
stem cells
gram negative
mesenchymal stem cells