Metadata-Version: 2.1
Name: torchio
Version: 0.16.4
Summary: Tools for loading, augmenting and writing 3D medical images on PyTorch.
Home-page: https://github.com/fepegar/torchio
Author: Fernando Perez-Garcia
Author-email: fernando.perezgarcia.17@ucl.ac.uk
License: MIT license
Description: # [TorchIO](http://torchio.rtfd.io/)
        
        [![PyPI downloads](https://img.shields.io/pypi/dm/torchio.svg?label=PyPI%20downloads&logo=python&logoColor=white)](https://pypi.org/project/torchio/)
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        ---
        
        ### 🎉 News: the paper is out! 🎉
        
        See the [Credits](#credits) section below for more information.
        
        ---
        
        <table align="center">
            <tr>
                <td align="center">Original</td>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomblur">Random blur</a>
                </td>
            </tr>
            <tr>
                <td align="center"><img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/1_Lambda_mri.png" alt="Original"></td>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomblur">
                        <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/2_RandomBlur_mri.gif" alt="Random blur">
                    </a>
                </td>
            </tr>
            <tr>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomflip">Random flip</a>
                </td>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomnoise">Random noise</a>
                </td>
            </tr>
            <tr>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomflip">
                        <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/3_RandomFlip_mri.gif" alt="Random flip">
                    </a>
                </td>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomnoise">
                        <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/4_Compose_mri.gif" alt="Random noise">
                    </a>
                </td>
            </tr>
            <tr>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomaffine">Random affine transformation</a>
                </td>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomelasticdeformation">Random elastic transformation</a>
                </td>
            </tr>
            <tr>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomaffine">
                        <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/5_RandomAffine_mri.gif" alt="Random affine transformation">
                    </a>
                </td>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomelasticdeformation">
                        <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/6_RandomElasticDeformation_mri.gif" alt="Random elastic transformation">
                    </a>
                </td>
            </tr>
            <tr>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randombiasfield">Random bias field artifact</a>
                </td>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randommotion">Random motion artifact</a>
                </td>
            </tr>
            <tr>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randombiasfield">
                        <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/7_RandomBiasField_mri.gif" alt="Random bias field artifact">
                    </a>
                </td>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randommotion">
                        <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/8_RandomMotion_mri.gif" alt="Random motion artifact">
                    </a>
                </td>
            </tr>
            <tr>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomspike">Random spike artifact</a>
                </td>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomghosting">Random ghosting artifact</a>
                </td>
            </tr>
            <tr>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomspike">
                        <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/9_RandomSpike_mri.gif" alt="Random spike artifact">
                    </a>
                </td>
                <td align="center">
                    <a href="http://torchio.rtfd.io/transforms/augmentation.html#randomghosting">
                        <img src="https://raw.githubusercontent.com/fepegar/torchio/master/docs/images/gifs_readme/10_RandomGhosting_mri.gif" alt="Random ghosting artifact">
                    </a>
                </td>
            </tr>
        </table>
        
        
        
        TorchIO is a Python package containing a set of tools to efficiently
        read, sample and write 3D medical images in deep learning applications
        written in [PyTorch](https://pytorch.org/),
        including intensity and spatial transforms
        for data augmentation and preprocessing.
        Transforms include typical computer vision operations
        such as random affine transformations and also domain-specific ones such as
        simulation of intensity artifacts due to
        [MRI magnetic field inhomogeneity](http://mriquestions.com/why-homogeneity.html)
        or [k-space motion artifacts](http://proceedings.mlr.press/v102/shaw19a.html).
        
        This package has been greatly inspired by [NiftyNet](https://niftynet.io/).
        
        
        ## [Documentation](http://torchio.rtfd.io/)
        
        The documentation is hosted on
        [Read the Docs](http://torchio.rtfd.io/).
        
        Please [create a new issue](https://github.com/fepegar/torchio/issues/new)
        if you think something is missing.
        
        
        ## Credits
        
        If you like this repository, please click on Star!
        
        If you use this package for your research, please cite the paper:
        
        [Pérez-García et al., 2020, *TorchIO: a Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning*](https://arxiv.org/abs/2003.04696).
        
        
        BibTeX entry:
        
        ```bibtex
        @misc{fern2020torchio,
            title={TorchIO: a Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning},
            author={Fernando Pérez-García and Rachel Sparks and Sebastien Ourselin},
            year={2020},
            eprint={2003.04696},
            archivePrefix={arXiv},
            primaryClass={eess.IV}
        }
        ```
        
        
        History
        =======
        
        0.15.0 (07-04-2020)
        -------------------
        
        * Refactor ``RandomElasticDeformation`` transform
        * Make ``Subject`` inherit from ``dict``
        
        
        0.14.0 (31-03-2020)
        -------------------
        
        * Add ``datasets`` module
        * Add support for DICOM files
        * Add documentation
        * Add ``CropOrPad`` transform
        
        
        0.13.0 (24-02-2020)
        -------------------
        
        * Add ``Subject`` class
        * Add random blur transform
        * Add lambda transform
        * Add random patches swapping transform
        * Add MRI k-space ghosting artefact augmentation
        
        
        0.12.0 (21-01-2020)
        -------------------
        
        * Add ToCanonical transform
        * Add CenterCropOrPad transform
        
        
        0.11.0 (15-01-2020)
        -------------------
        
        * Add Resample transform
        
        
        0.10.0 (15-01-2020)
        -------------------
        
        * Add Pad transform
        * Add Crop transform
        
        
        0.9.0 (14-01-2020)
        ------------------
        
        * Add CLI tool to transform an image from file
        
        
        0.8.0 (11-01-2020)
        ------------------
        
        * Add Image class
        
        
        0.7.0 (02-01-2020)
        ------------------
        
        * Make transforms use PyTorch tensors consistently
        
        
        0.6.0 (02-01-2020)
        ------------------
        
        * Add support for NRRD
        
        
        0.5.0 (01-01-2020)
        ------------------
        
        * Add bias field transform
        
        
        0.4.0 (29-12-2019)
        ------------------
        
        * Add MRI k-space motion artefact augmentation
        
        
        0.3.0 (21-12-2019)
        ------------------
        
        * Add Rescale transform
        * Add support for multimodal data and missing modalities
        
        
        0.2.0 (2019-12-06)
        ------------------
        
        * First release on PyPI.
        
Keywords: torchio
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
Description-Content-Type: text/markdown
