fastMRI download for Linux

This is the Linux app named fastMRI whose latest release can be downloaded as Bugfixreleasesourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.

 
 

Download and run online this app named fastMRI with OnWorks for free.

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- 1. Download deze applicatie op uw pc.

- 2. Voer in onze bestandsbeheerder https://www.onworks.net/myfiles.php?username=XXXXX in met de gebruikersnaam die u wilt.

- 3. Upload deze applicatie in zo'n bestandsbeheerder.

- 4. Start de OnWorks Linux online of Windows online emulator of MACOS online emulator vanaf deze website.

- 5. Ga vanuit het OnWorks Linux-besturingssysteem dat u zojuist hebt gestart naar onze bestandsbeheerder https://www.onworks.net/myfiles.php?username=XXXXX met de gewenste gebruikersnaam.

- 6. Download de applicatie, installeer hem en voer hem uit.

SCHERMSCHERMEN:


snelle MRI


BESCHRIJVING:

fastMRI is a large-scale collaborative research project by Facebook AI Research (FAIR) and NYU Langone Health that explores how deep learning can accelerate magnetic resonance imaging (MRI) acquisition without compromising image quality. By enabling reconstruction of high-fidelity MR images from significantly fewer measurements, fastMRI aims to make MRI scanning faster, cheaper, and more accessible in clinical settings. The repository provides an open-source PyTorch framework with data loaders, subsampling utilities, reconstruction models, and evaluation metrics, supporting both research reproducibility and practical experimentation. It includes reference implementations for key MRI reconstruction architectures such as U-Net and Variational Networks (VarNet), along with example scripts for model training and evaluation using the PyTorch Lightning framework. The project also releases several fully anonymized public MRI datasets, including knee, brain, and prostate scans.



Kenmerken

  • Open source PyTorch framework for accelerated MRI reconstruction research
  • Includes MRI datasets (knee, brain, prostate) with raw k-space and DICOM data
  • Provides U-Net, VarNet, and ESPIRiT-based reconstruction models
  • Offers standardized evaluation metrics and reproducible training pipelines
  • Compatible with PyTorch Lightning for modular training and logging
  • Benchmarks from major publications and challenge datasets included


Programmeertaal

Python


Categorieën

Libraries, Deep Learning Frameworks

This is an application that can also be fetched from https://sourceforge.net/projects/fastmri.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.



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