Registration by Regression (RbR): a framework for interpretable and flexible atlas registration Article Swipe
Karthik Gopinath
,
Xiaoling Hu
,
Malte Hoffmann
,
Oula Puonti
,
Juan Eugenio Iglesias
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2404.16781
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2404.16781
In human neuroimaging studies, atlas registration enables mapping MRI scans to a common coordinate frame, which is necessary to aggregate data from multiple subjects. Machine learning registration methods have achieved excellent speed and accuracy but lack interpretability and flexibility at test time (since their deformation model is fixed). More recently, keypoint-based methods have been proposed to tackle these issues, but their accuracy is still subpar, particularly when fitting nonlinear transforms. Here we propose Registration by Regression (RbR), a novel atlas registration framework that: is highly robust and flexible; can be trained with cheaply obtained data; and operates on a single channel, such that it can also be used as pretraining for other tasks. RbR predicts the (x, y, z) atlas coordinates for every voxel of the input scan (i.e., every voxel is a keypoint), and then uses closed-form expressions to quickly fit transforms using a wide array of possible deformation models, including affine and nonlinear (e.g., Bspline, Demons, invertible diffeomorphic models, etc.). Robustness is provided by the large number of voxels informing the registration and can be further increased by robust estimators like RANSAC. Experiments on independent public datasets show that RbR yields more accurate registration than competing keypoint approaches, over a wide range of deformation models.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2404.16781
- https://arxiv.org/pdf/2404.16781
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4395687426
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4395687426Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2404.16781Digital Object Identifier
- Title
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Registration by Regression (RbR): a framework for interpretable and flexible atlas registrationWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
-
2024-04-25Full publication date if available
- Authors
-
Karthik Gopinath, Xiaoling Hu, Malte Hoffmann, Oula Puonti, Juan Eugenio IglesiasList of authors in order
- Landing page
-
https://arxiv.org/abs/2404.16781Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2404.16781Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2404.16781Direct OA link when available
- Concepts
-
Atlas (anatomy), Regression, Artificial intelligence, Computer science, Cartography, Geography, Statistics, Medicine, Mathematics, AnatomyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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