Skip to main content

Generative image priors for MRI image reconstruction

Project description

Speed up MR scanner with generative priors for image reconstruction (SPRECO)

workflow This package is to help you train generative image priors of MRI images and then use them in image reconstruction. It has the following features:
  1. Distributed training
  2. Interruptible training
  3. Efficient dataloader for medical images
  4. Customizable with a configuration file
  5. Seamless deployment with BART

Installation: Clone this repository and use conda to set up the environment.

$ git clone https://github.com/mrirecon/spreco.git
$ cd spreco
$ pip install .

Reference

We would appreciate it if you tried our codes and cited our work.

[1] G. Luo, X. Wang, M. Blumenthal, M. Schilling, EHU. Rauf, R. Kotikalapudi, NK. Focke, M. Uecker. Generative image priors for MRI reconstruction trained from magnitude-only images. arXiv preprint arXiv:2308.02340 (2023)

[2] G. Luo, M. Blumenthal, M. Heide, M. Uecker. Bayesian MRI reconstruction with joint uncertainty estimation using diffusion models. Magn Reson Med. 2023; 1-17

[3] M. Blumenthal, G. Luo, M. Schilling, HCM. Holme, M. Uecker. Deep, deep learning with BART. Magn Reson Med. 2023; 89: 678- 693.

[4] G. Luo, N. Zhao, W. Jiang, ES. Hui, P. Cao. MRI reconstruction using deep Bayesian estimation. Magn Reson Med. 2020; 84: 2246-2261.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

spreco-0.0.4.tar.gz (57.8 kB view details)

Uploaded Source

Built Distribution

spreco-0.0.4-py3-none-any.whl (69.8 kB view details)

Uploaded Python 3

File details

Details for the file spreco-0.0.4.tar.gz.

File metadata

  • Download URL: spreco-0.0.4.tar.gz
  • Upload date:
  • Size: 57.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.2

File hashes

Hashes for spreco-0.0.4.tar.gz
Algorithm Hash digest
SHA256 88746ff890cd10f6a3aac048fbbd62ae79a5cfdd118ca135785336c9d6500f05
MD5 d7d7a0198e93293ddc4411db6fc7a688
BLAKE2b-256 3f777bf234f6ab11d00cd1f08ac87746297127b9be68c0b2b51102e3e4ec9b48

See more details on using hashes here.

File details

Details for the file spreco-0.0.4-py3-none-any.whl.

File metadata

  • Download URL: spreco-0.0.4-py3-none-any.whl
  • Upload date:
  • Size: 69.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.2

File hashes

Hashes for spreco-0.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 d75bbdc1f7bc89a783baac4b3f420875ead6c4aea890e3877ff81fbd0bab00d1
MD5 cdfb4b47b3253db54233aecb4505891f
BLAKE2b-256 ac6b84890433a33fa42d8b007852572a7de64f01ab2f40c12cea274a06f6a85b

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page