RT Journal Article
SR Electronic
T1 DeepMIB: User-friendly and open-source software for training of deep learning network for biological image segmentation
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.07.13.200105
DO 10.1101/2020.07.13.200105
A1 Belevich, Ilya
A1 Jokitalo, Eija
YR 2020
UL http://biorxiv.org/content/early/2020/07/14/2020.07.13.200105.abstract
AB Deep learning approaches are highly sought after solutions for coping with large amounts of collected datasets and are expected to become an essential part of imaging workflows. However, in most cases, deep learning is still considered as a complex task that only image analysis experts can master. DeepMIB addresses this problem and provides the community with a user-friendly and open-source tool to train convolutional neural networks and apply them to segment 2D and 3D light and electron microscopy datasets.Competing Interest StatementThe authors have declared no competing interest.