A collection of TensorFlow add-ons for computational MRI.
Project description
TensorFlow MRI (TFMR) is a Python library for MR image reconstruction and processing. TFMR provides:
A selection of differentiable operators for accelerated image reconstruction, Cartesian and non-Cartesian k-space sampling, and many other common MR image and signal processing tasks.
Keras callbacks, layers, metrics and losses and other utilities for the creation, training and evaluation of machine learning models.
TFMR is aimed for scientists and researchers working with MRI data. Whether you are planning to use machine learning or not, TFMR enables prototyping and deployment of efficient computational MRI solutions easily and within Python.
Thanks to the use of a TensorFlow backend, TFMR integrates seamlessly in machine learning projects. It also inherits other benefits of TensorFlow, including high performance computation and GPU acceleration.
Installation
You can install TensorFlow MRI with pip:
$ pip install tensorflow-mriNote that only Linux is currently supported.
TensorFlow Compatibility
Each TensorFlow MRI release is compiled against a specific version of TensorFlow. To ensure compatibility, it is recommended to install matching versions of TensorFlow and TensorFlow MRI according to the table below.
TensorFlow MRI Version |
TensorFlow Compatibility |
Release Date |
|---|---|---|
v0.8.0 |
v2.7.x |
Nov 11, 2021 |
v0.7.0 |
v2.6.x |
Nov 3, 2021 |
v0.6.2 |
v2.6.x |
Oct 13, 2021 |
v0.6.1 |
v2.6.x |
Sep 30, 2021 |
v0.6.0 |
v2.6.x |
Sep 28, 2021 |
v0.5.0 |
v2.6.x |
Aug 29, 2021 |
v0.4.0 |
v2.6.x |
Aug 18, 2021 |
Documentation
Visit the docs for the API reference and examples of usage.
Contributions
If you use this package and something does not work as you expected, please file an issue describing your problem. We will do our best to help.
Contributions are very welcome. Please create a pull request if you would like to make a contribution.
Citation
If you find this software useful in your work, please cite us.
FAQ
When trying to install TensorFlow MRI, I get an error about OpenEXR which includes: ``OpenEXR.cpp:36:10: fatal error: ImathBox.h: No such file or directory``. What do I do?
OpenEXR is needed by TensorFlow Graphics, which is a dependency of TensorFlow MRI. This issue can be fixed by installing the OpenEXR library. On Debian/Ubuntu:
$ apt install libopenexr-devRelease history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distributions
Hashes for tensorflow_mri-0.8.0-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 524dffe0b4dd99de31b74a5f706fa6da7195afc459b39ff2b013157ab3eac9f0 |
|
| MD5 | f6d702db0c8b54b0519d4da31d883967 |
|
| BLAKE2b-256 | ad2114e572aee9660646d34e4ded45b2cabbac2f2113492ed1ec7c0124342e15 |
Hashes for tensorflow_mri-0.8.0-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 0782cb7c929a5d71b2b129659d56fac899473c8184d89f247f28799deeec1937 |
|
| MD5 | bbe21973829aaabfdfabce15f5a8d2d8 |
|
| BLAKE2b-256 | 3692d7fe82eff358c2bd83e09103af6a4aef89aa3cb5572d789233450a265e6d |
Hashes for tensorflow_mri-0.8.0-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 4f794723e49d5489539c2c0594f5fec9de3ac7d9c78ac6230395ff4380148203 |
|
| MD5 | 1eacc71dc3546946f60deaaf5a3b8304 |
|
| BLAKE2b-256 | 5b61209d554605c2858d856a60e6270b08aac55bf2d9df24b182fcf33d38059e |
