Automated Training of Deep Convolutional Neural Networks for Cell Segmentation.

ABSTRACT: Deep Convolutional Neural Networks (DCNN) have recently emerged as superior for many image segmentation tasks. The DCNN performance is however heavily dependent on the availability of large amounts of problem-specific training samples. Here we show that DCNNs trained on ground truth created automatically using fluorescently labeled cells, perform similar to manual annotations.

SUBMITTER: Sadanandan SK 

PROVIDER: S-EPMC5552800 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature