RegBoost: Enhancing mouse brain image registration using geometric priors and Laplacian interpolation
We show in this work that incorporating geometric features and geometry processing algorithms for mouse brain image registration broadens the applicability of registration algorithms and improves the registration accuracy of existing methods. We introduce the preprocessing and postprocessing steps i...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | NeuroImage |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811924004786 |
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| author | Atchuth Naveen Chilaparasetti Andy Thai Pan Gao Xiangmin Xu M. Gopi |
| author_facet | Atchuth Naveen Chilaparasetti Andy Thai Pan Gao Xiangmin Xu M. Gopi |
| author_sort | Atchuth Naveen Chilaparasetti |
| collection | DOAJ |
| description | We show in this work that incorporating geometric features and geometry processing algorithms for mouse brain image registration broadens the applicability of registration algorithms and improves the registration accuracy of existing methods. We introduce the preprocessing and postprocessing steps in our proposed framework as RegBoost. We develop a method to align the axis of 3D image stacks by detecting the central planes that pass symmetrically through the image volumes. We then find geometric contours by defining external and internal structures to facilitate image correspondences. We establish Dirichlet boundary conditions at these correspondences and find the displacement map throughout the volume using Laplacian interpolation. We discuss the challenges in our standalone framework and demonstrate how our new approaches can improve the results of existing image registration methods. We expect our new approach and algorithms will have critical applications in brain mapping projects. |
| format | Article |
| id | doaj-art-85bfcb68cad140408993b470478e0214 |
| institution | Kabale University |
| issn | 1095-9572 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj-art-85bfcb68cad140408993b470478e02142025-01-11T06:38:34ZengElsevierNeuroImage1095-95722025-01-01305120981RegBoost: Enhancing mouse brain image registration using geometric priors and Laplacian interpolationAtchuth Naveen Chilaparasetti0Andy Thai1Pan Gao2Xiangmin Xu3M. Gopi4Department of Computer Science, University of California, Irvine, Irvine, CA 92617, USADepartment of Computer Science, University of California, Irvine, Irvine, CA 92617, USA; Corresponding authors.Department of Anatomy and Neurobiology, School of Medicine, University of California, Irvine, Irvine, CA 92617, USADepartment of Computer Science, University of California, Irvine, Irvine, CA 92617, USA; Department of Anatomy and Neurobiology, School of Medicine, University of California, Irvine, Irvine, CA 92617, USADepartment of Computer Science, University of California, Irvine, Irvine, CA 92617, USA; Corresponding authors.We show in this work that incorporating geometric features and geometry processing algorithms for mouse brain image registration broadens the applicability of registration algorithms and improves the registration accuracy of existing methods. We introduce the preprocessing and postprocessing steps in our proposed framework as RegBoost. We develop a method to align the axis of 3D image stacks by detecting the central planes that pass symmetrically through the image volumes. We then find geometric contours by defining external and internal structures to facilitate image correspondences. We establish Dirichlet boundary conditions at these correspondences and find the displacement map throughout the volume using Laplacian interpolation. We discuss the challenges in our standalone framework and demonstrate how our new approaches can improve the results of existing image registration methods. We expect our new approach and algorithms will have critical applications in brain mapping projects.http://www.sciencedirect.com/science/article/pii/S1053811924004786RegistrationGeometry processingLaplacianMouse brainNeuroimaging |
| spellingShingle | Atchuth Naveen Chilaparasetti Andy Thai Pan Gao Xiangmin Xu M. Gopi RegBoost: Enhancing mouse brain image registration using geometric priors and Laplacian interpolation NeuroImage Registration Geometry processing Laplacian Mouse brain Neuroimaging |
| title | RegBoost: Enhancing mouse brain image registration using geometric priors and Laplacian interpolation |
| title_full | RegBoost: Enhancing mouse brain image registration using geometric priors and Laplacian interpolation |
| title_fullStr | RegBoost: Enhancing mouse brain image registration using geometric priors and Laplacian interpolation |
| title_full_unstemmed | RegBoost: Enhancing mouse brain image registration using geometric priors and Laplacian interpolation |
| title_short | RegBoost: Enhancing mouse brain image registration using geometric priors and Laplacian interpolation |
| title_sort | regboost enhancing mouse brain image registration using geometric priors and laplacian interpolation |
| topic | Registration Geometry processing Laplacian Mouse brain Neuroimaging |
| url | http://www.sciencedirect.com/science/article/pii/S1053811924004786 |
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