SPIRiT Regularization: Parallel MRI with a Combination of Sensitivity Encoding and Linear Predictability
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866912546364063744 |
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| author | Dwork, Nicholas McManus, Alex Becker, Stephen Smith, Gennifer T. |
| author_facet | Dwork, Nicholas McManus, Alex Becker, Stephen Smith, Gennifer T. |
| contents | Accelerated Magnetic Resonance Imaging (MRI) permits high quality images from fewer samples that can be collected with a faster scan. Two established methods for accelerating MRI include parallel imaging and compressed sensing. Two types of parallel imaging include linear predictability, which assumes that the Fourier samples are linearly related, and sensitivity encoding, which incorporates a priori knowledge of the sensitivity maps. In this work, we combine compressed sensing with both types of parallel imaging using a novel regularization term: SPIRiT regularization. When combined, the reconstructed images are improved. We demonstrate results on data of a brain, a knee, and an ankle. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_15132 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | SPIRiT Regularization: Parallel MRI with a Combination of Sensitivity Encoding and Linear Predictability Dwork, Nicholas McManus, Alex Becker, Stephen Smith, Gennifer T. Image and Video Processing Accelerated Magnetic Resonance Imaging (MRI) permits high quality images from fewer samples that can be collected with a faster scan. Two established methods for accelerating MRI include parallel imaging and compressed sensing. Two types of parallel imaging include linear predictability, which assumes that the Fourier samples are linearly related, and sensitivity encoding, which incorporates a priori knowledge of the sensitivity maps. In this work, we combine compressed sensing with both types of parallel imaging using a novel regularization term: SPIRiT regularization. When combined, the reconstructed images are improved. We demonstrate results on data of a brain, a knee, and an ankle. |
| title | SPIRiT Regularization: Parallel MRI with a Combination of Sensitivity Encoding and Linear Predictability |
| topic | Image and Video Processing |
| url | https://arxiv.org/abs/2508.15132 |