A GPU-enhanced workflow for non-Fourier SENSE reconstruction
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
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2026
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| _version_ | 1866911581676240896 |
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| author | Bianchi, Samuel Pruessmann, Klaas P. |
| author_facet | Bianchi, Samuel Pruessmann, Klaas P. |
| contents | Purpose: Image reconstruction in challenging scenarios requires accurate characterisations of coil sensitivity profiles, local off-resonances (B0) and effective encoding fields. Reconstruction methods utilising all of this information rely on signal models that are not compatible with the classical Fourier/k-space interpretation of the coil data. Hence, the FFT and related techniques are no more applicable, rendering image reconstruction computationally demanding.
Methods: This article contains a workflow for accurate sensitivity and B0 mapping as well as other required processing steps. An implementation of non-Fourier SENSE reconstruction is provide that is well suited for execution on a GPU using the FFT. Important practical aspects like stopping criteria and sources of image artifacts are analyzed and documented.
Results: Highly performant image reconstruction could be demonstrated on a 2D and 3D spiral dataset. These datasets contain trajectories featuring readout durations up to 71.5ms and undersampling factors up to R = 7. Running the reconstruction on a GPU greatly boosts reconstruction speed. Stopping the reconstruction at the right moment is crucial for image quality. All methods included in this article are available in a public code repository.
Conclusion: The provided implementation of non-Fourier SENSE reconstruction is highly performant. When it is executed on GPU, runtimes reach a duration feasible in practice. The presented workflow ensures robust and accurate computation of coil sensitive profiles and off-resonance maps. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_09233 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A GPU-enhanced workflow for non-Fourier SENSE reconstruction Bianchi, Samuel Pruessmann, Klaas P. Image and Video Processing Purpose: Image reconstruction in challenging scenarios requires accurate characterisations of coil sensitivity profiles, local off-resonances (B0) and effective encoding fields. Reconstruction methods utilising all of this information rely on signal models that are not compatible with the classical Fourier/k-space interpretation of the coil data. Hence, the FFT and related techniques are no more applicable, rendering image reconstruction computationally demanding. Methods: This article contains a workflow for accurate sensitivity and B0 mapping as well as other required processing steps. An implementation of non-Fourier SENSE reconstruction is provide that is well suited for execution on a GPU using the FFT. Important practical aspects like stopping criteria and sources of image artifacts are analyzed and documented. Results: Highly performant image reconstruction could be demonstrated on a 2D and 3D spiral dataset. These datasets contain trajectories featuring readout durations up to 71.5ms and undersampling factors up to R = 7. Running the reconstruction on a GPU greatly boosts reconstruction speed. Stopping the reconstruction at the right moment is crucial for image quality. All methods included in this article are available in a public code repository. Conclusion: The provided implementation of non-Fourier SENSE reconstruction is highly performant. When it is executed on GPU, runtimes reach a duration feasible in practice. The presented workflow ensures robust and accurate computation of coil sensitive profiles and off-resonance maps. |
| title | A GPU-enhanced workflow for non-Fourier SENSE reconstruction |
| topic | Image and Video Processing |
| url | https://arxiv.org/abs/2604.09233 |