King's College London
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TMISynCode.zip (303.81 MB)

Randomised high resolution 4D volumes synthesis

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posted on 2021-09-13, 18:33 authored by Xin Chen, Andrew King, Claudia Prieto Vasquez, Daniel Robert Malcolm Balfour, Andrew Jonathan Reader, Paul Kenneth Marsden, Muhammad Usman, Christian Baumgartner
- EPSRC funded project to investigate machine learning based methods to use MR data for motion correction of PET data - Data acquired from healthy volunteer with ethics and consent - Code does not have warranty and for research purpose only - Code is written in Matlab - Associated publication: X. Chen et al., 'High-Resolution Self-Gated Dynamic Abdominal MRI Using Manifold Alignment', IEEE Transactions on Medical Imaging, 2017.
- Approx 300 MB in total
- File formats: - .m : Matlab source files - .mat: Matlab binary file - .c : C source file - .mexa64 : Matlab binary MEX file

Funding

EPSRC

PET-MR Motion Correction Based Purely on Routine Clinical Scans

Engineering and Physical Sciences Research Council

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History

Language

English

Copyright owner

Copyright - Andrew King