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Automated quantification of fibrous networks

Project description

Qiber3D

Automated quantification of fibrous networks

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Binder Binder

Setup

pip install Qiber3D

You can install the latest version

pip install -U git+https://github.com/theia-dev/Qiber3D.git#egg=Qiber3D

or the dev version directly from GitHub.

pip install -U git+https://github.com/theia-dev/Qiber3D.git@dev#egg=Qiber3D

Quick usage

An image stack or a preprocessed network can be loaded with Network.load() To follow this example, you can download the image stack from figshare under doi:10.6084/m9.figshare.13655606 or use the Example class.

import logging
from Qiber3D import Network, config
from Qiber3D.helper import Example, change_log_level

config.extract.nd2_channel_name = 'FITC'
change_log_level(logging.DEBUG)

net_ex = Example.nd2()
net = Network.load(net_ex)
print(net)
# Input file: microvascular_network.nd2
#   Number of fibers: 459 (clustered 97)
#   Number of segments: 660
#   Number of branch points: 130
#   Total length: 16056.46
#   Total volume: 1240236.70
#   Average radius: 4.990
#   Cylinder radius: 4.959
#   Bounding box volume: 681182790

net.save(save_steps=True)
# Qiber3D_core [INFO] Network saved to Exp190309_PrMECs-NPF180_gel4_ROI-c.qiber

net.render.show()
net.render.compare()

A more extensive interactive example is available as a Jupyter notebook. You can try it out directly on Binder. More in-depth documentation, including details on the inner working, can be found at Read the docs.

The complete source code is available on GitHub.

Project details


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