===========================
Scipion plugin for cryoCARE
===========================
.. image:: https://img.shields.io/pypi/v/scipion-em-cryocare.svg
:target: https://pypi.python.org/pypi/scipion-em-cryocare
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.. image:: https://img.shields.io/pypi/l/scipion-em-cryocare.svg
:target: https://pypi.python.org/pypi/scipion-em-cryocare
:alt: License
.. image:: https://img.shields.io/pypi/pyversions/scipion-em-cryocare.svg
:target: https://pypi.python.org/pypi/scipion-em-cryocare
:alt: Supported Python versions
.. image:: https://img.shields.io/pypi/dm/scipion-em-cryocare
:target: https://pypi.python.org/pypi/scipion-em-cryocare
:alt: Downloads
This plugin allows to use cryoCARE_ -trains a denoising U-Net for tomographic reconstruction according to the
Noise2Noise_ training paradigm- tomography methods into Scipion framework.
============
Installation
============
The plugin can be installed in user (stable) or developer (latest, may be unstable) mode:
**1. User (stable) version:**:
.. code-block::
scipion3 installp -p scipion-em-cryocare
**2. Developer (latest, may be unstable) version:**:
* Clone the source code repository:
.. code-block::
git clone https://github.com/scipion-em/scipion-em-cryocare.git
* Install:
.. code-block::
scipion3 installp -p local/path/to/scipion-em-cryocare --devel
=========
Protocols
=========
The integrated protocols are:
1. Load a previously trained model.
2. Generate the training data.
3. Training: uses two data-independent reconstructed tomograms to train a 3D cryoCARE network.
4. Predict: generates the final restored tomogram by applying the cryoCARE trained network to both
even/odd tomograms followed by per-pixel averaging.
=====
Tests
=====
The installation can be checked out running some tests. To list all of them, execute:
.. code-block::
scipion3 tests --grep cryocare
To run all of them, execute:
.. code-block::
scipion3 tests --grep cryocare --run
========
Tutorial
========
The test generates a cryoCARE workflow that can be used as a guide about how to use cryoCARE. The even/odd tomograms
required to use cryoCARE can be generated inside Scipion with:
1. Plugin scipion-em-motioncorr_: protocol "align tilt-series movies".
2. Plugin scipion-em-xmipptomo_: protocol "tilt-series flexalign".
==========
References
==========
* `Cryo-CARE: Content-Aware Image Restoration for Cryo-Transmission Electron Microscopy Data. <http://doi.org/10.1109/ISBI.2019.8759519>`_
Tim-Oliver Buchholz et al., 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).
===================
Contact information
===================
If you experiment any problem, please contact us here: scipion-users@lists.sourceforge.net or open an issue_.
We'll be pleased to help.
*Scipion Team*
.. _cryoCARE: https://github.com/juglab/cryoCARE_pip
.. _Noise2Noise: https://arxiv.org/pdf/1803.04189.pdf
.. _scipion-em-motioncorr: https://github.com/scipion-em/scipion-em-motioncorr
.. _scipion-em-xmipptomo: https://github.com/I2PC/scipion-em-xmipptomo
.. _issue: https://github.com/scipion-em/scipion-em-cryocare/issues
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"description": "===========================\nScipion plugin for cryoCARE\n===========================\n\n.. image:: https://img.shields.io/pypi/v/scipion-em-cryocare.svg\n :target: https://pypi.python.org/pypi/scipion-em-cryocare\n :alt: PyPI release\n\n.. image:: https://img.shields.io/pypi/l/scipion-em-cryocare.svg\n :target: https://pypi.python.org/pypi/scipion-em-cryocare\n :alt: License\n\n.. image:: https://img.shields.io/pypi/pyversions/scipion-em-cryocare.svg\n :target: https://pypi.python.org/pypi/scipion-em-cryocare\n :alt: Supported Python versions\n\n.. image:: https://img.shields.io/pypi/dm/scipion-em-cryocare\n :target: https://pypi.python.org/pypi/scipion-em-cryocare\n :alt: Downloads\n\nThis plugin allows to use cryoCARE_ -trains a denoising U-Net for tomographic reconstruction according to the\nNoise2Noise_ training paradigm- tomography methods into Scipion framework.\n\n============\nInstallation\n============\nThe plugin can be installed in user (stable) or developer (latest, may be unstable) mode:\n\n**1. User (stable) version:**:\n\n.. code-block::\n\n scipion3 installp -p scipion-em-cryocare\n\n**2. Developer (latest, may be unstable) version:**:\n\n* Clone the source code repository:\n\n.. code-block::\n\n git clone https://github.com/scipion-em/scipion-em-cryocare.git\n\n* Install:\n\n.. code-block::\n\n scipion3 installp -p local/path/to/scipion-em-cryocare --devel\n\n=========\nProtocols\n=========\nThe integrated protocols are:\n\n1. Load a previously trained model.\n\n2. Generate the training data.\n\n3. Training: uses two data-independent reconstructed tomograms to train a 3D cryoCARE network.\n\n4. Predict: generates the final restored tomogram by applying the cryoCARE trained network to both\neven/odd tomograms followed by per-pixel averaging.\n\n=====\nTests\n=====\n\nThe installation can be checked out running some tests. To list all of them, execute:\n\n.. code-block::\n\n scipion3 tests --grep cryocare\n\nTo run all of them, execute:\n\n.. code-block::\n\n scipion3 tests --grep cryocare --run\n\n========\nTutorial\n========\n\nThe test generates a cryoCARE workflow that can be used as a guide about how to use cryoCARE. The even/odd tomograms\nrequired to use cryoCARE can be generated inside Scipion with:\n\n1. Plugin scipion-em-motioncorr_: protocol \"align tilt-series movies\".\n\n2. Plugin scipion-em-xmipptomo_: protocol \"tilt-series flexalign\".\n\n==========\nReferences\n==========\n\n* `Cryo-CARE: Content-Aware Image Restoration for Cryo-Transmission Electron Microscopy Data. <http://doi.org/10.1109/ISBI.2019.8759519>`_\n Tim-Oliver Buchholz et al., 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).\n\n===================\nContact information\n===================\n\nIf you experiment any problem, please contact us here: scipion-users@lists.sourceforge.net or open an issue_.\n\nWe'll be pleased to help.\n\n*Scipion Team*\n\n\n.. _cryoCARE: https://github.com/juglab/cryoCARE_pip\n.. _Noise2Noise: https://arxiv.org/pdf/1803.04189.pdf\n.. _scipion-em-motioncorr: https://github.com/scipion-em/scipion-em-motioncorr\n.. _scipion-em-xmipptomo: https://github.com/I2PC/scipion-em-xmipptomo\n.. _issue: https://github.com/scipion-em/scipion-em-cryocare/issues",
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