vanvalenlab/deepcell-tf
A TensorFlow 2 library for single-cell analysis providing deep learning models for cell segmentation and tracking in biological imaging data.
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This library provides pre-existing deep learning models for cell segmentation (nuclear and whole-cell) in 2D and 3D images, as well as cell tracking in time-lapse datasets. Users can apply these models to biological imaging data or develop new custom models using TensorFlow 2 as the underlying framework. It targets multiplexed tissue images and live-cell imaging movies.
Frequently asked
- What is vanvalenlab/deepcell-tf?
- A TensorFlow 2 library for single-cell analysis providing deep learning models for cell segmentation and tracking in biological imaging data.
- Is deepcell-tf open source?
- Yes — vanvalenlab/deepcell-tf is open source, released under the Apache-2.0 license.
- What language is deepcell-tf written in?
- vanvalenlab/deepcell-tf is primarily written in Python.
- How popular is deepcell-tf?
- vanvalenlab/deepcell-tf has 475 stars on GitHub.
- Where can I find deepcell-tf?
- vanvalenlab/deepcell-tf is on GitHub at https://github.com/vanvalenlab/deepcell-tf.