Scan-Adaptive MRI Undersampling Using Neighbor-based Optimization (SUNO) Article Swipe
Siddhant Gautam
,
Angqi Li
,
Nicole Seiberlich
,
Jeffrey A. Fessler
,
Saiprasad Ravishankar
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2501.09799
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2501.09799
Accelerated MRI involves collecting partial $k$-space measurements to reduce acquisition time, patient discomfort, and motion artifacts, and typically uses regular undersampling patterns or human-designed schemes. Recent works have studied population-adaptive sampling patterns learned from a group of patients (or scans). However, such patterns can be sub-optimal for individual scans, as they may fail to capture scan or slice-specific details, and their effectiveness can depend on the size and composition of the population. To overcome this issue, we propose a framework for jointly learning scan-adaptive Cartesian undersampling patterns and a corresponding reconstruction model from a training set. We use an alternating algorithm for learning the sampling patterns and the reconstruction model where we use an iterative coordinate descent (ICD) based offline optimization of scan-adaptive $k$-space sampling patterns for each example in the training set. A nearest neighbor search is then used to select the scan-adaptive sampling pattern at test time from initially acquired low-frequency $k$-space information. We applied the proposed framework (dubbed SUNO) to the fastMRI multi-coil knee and brain datasets, demonstrating improved performance over the currently used undersampling patterns at both $4\times$ and $8\times$ acceleration factors in terms of both visual quality and quantitative metrics. The code for the proposed framework is available at https://github.com/sidgautam95/adaptive-sampling-mri-suno.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2501.09799
- https://arxiv.org/pdf/2501.09799
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4406603785
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4406603785Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2501.09799Digital Object Identifier
- Title
-
Scan-Adaptive MRI Undersampling Using Neighbor-based Optimization (SUNO)Work title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-01-16Full publication date if available
- Authors
-
Siddhant Gautam, Angqi Li, Nicole Seiberlich, Jeffrey A. Fessler, Saiprasad RavishankarList of authors in order
- Landing page
-
https://arxiv.org/abs/2501.09799Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2501.09799Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2501.09799Direct OA link when available
- Concepts
-
Undersampling, Computer science, Artificial intelligence, Pattern recognition (psychology)Top concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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