bioRxiv · 10.1101/2020.07.13.200105
DeepMIB: User-friendly and open-source software for training of deep learning network for biological image segmentation
Abstract
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.
Source connections
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Belevich, I., Jokitalo, E.. 2020-07-14. DeepMIB: User-friendly and open-source software for training of deep learning network for biological image segmentation. https://doi.org/10.1101/2020.07.13.200105
Cite the original work for its findings. Save a collection to share your selection of sources.