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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.16214 |
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| _version_ | 1866910499619209216 |
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| author | Dwork, Nicholas Englund, Erin K. Barker, Alex J. |
| author_facet | Dwork, Nicholas Englund, Erin K. Barker, Alex J. |
| contents | With Fourier sensing, it is commonly the case that the field-of-view (FOV), the area of space to be imaged, is known prior to reconstruction. To date, reconstruction algorithms have focused on FOVs with simple geometries: a rectangle or a hexagon. This yields sampling patterns that are more burdensome than necessary. Due to the reduced area of imaging possible with an arbitrary (e.g., non-rectangular) FOV, the number of samples required for a high-quality images is reduced. However, when an arbitrary FOV has been considered, the reconstruction algorithm is computationally expensive. In this manuscript, we present a method to reduce the sampling pattern for an arbitrary FOV with an accompanying direct (non-iterative) reconstruction algorithm. We also present a method to decrease the computational cost of the (iterative) model-based reconstruction (MBR) algorithm. We present results using MRI data of an ankle, a pineapple, and a brain. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_16214 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Reducing the Sampling Burden of Fourier Sensing with a Non-rectangular Field-of-View Dwork, Nicholas Englund, Erin K. Barker, Alex J. Image and Video Processing With Fourier sensing, it is commonly the case that the field-of-view (FOV), the area of space to be imaged, is known prior to reconstruction. To date, reconstruction algorithms have focused on FOVs with simple geometries: a rectangle or a hexagon. This yields sampling patterns that are more burdensome than necessary. Due to the reduced area of imaging possible with an arbitrary (e.g., non-rectangular) FOV, the number of samples required for a high-quality images is reduced. However, when an arbitrary FOV has been considered, the reconstruction algorithm is computationally expensive. In this manuscript, we present a method to reduce the sampling pattern for an arbitrary FOV with an accompanying direct (non-iterative) reconstruction algorithm. We also present a method to decrease the computational cost of the (iterative) model-based reconstruction (MBR) algorithm. We present results using MRI data of an ankle, a pineapple, and a brain. |
| title | Reducing the Sampling Burden of Fourier Sensing with a Non-rectangular Field-of-View |
| topic | Image and Video Processing |
| url | https://arxiv.org/abs/2406.16214 |