Methods based on Radon transform for non-affine deformable image registration of noisy images
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866909302065725440 |
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| author | Hurtado, Daniel E. Osses, Axel Quezada, Rodrigo |
| author_facet | Hurtado, Daniel E. Osses, Axel Quezada, Rodrigo |
| contents | Deformable image registration is a standard engineering problem used to determine the distortion experienced by a body by comparing two images of it in different states. This study introduces two new DIR methods designed to capture non-affine deformations using Radon transform-based similarity measures and a classical regularizer based on linear elastic deformation energy. It establishes conditions for the existence and uniqueness of solutions for both methods and presents synthetic experimental results comparing them with a standard method based on the sum of squared differences similarity measure. These methods have been tested to capture various non-affine deformations in images, both with and without noise, and their convergence rates have been analyzed. Furthermore, the effectiveness of these methods was also evaluated in a lung image registration scenario. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_00037 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Methods based on Radon transform for non-affine deformable image registration of noisy images Hurtado, Daniel E. Osses, Axel Quezada, Rodrigo Computer Vision and Pattern Recognition Numerical Analysis Analysis of PDEs Optimization and Control Deformable image registration is a standard engineering problem used to determine the distortion experienced by a body by comparing two images of it in different states. This study introduces two new DIR methods designed to capture non-affine deformations using Radon transform-based similarity measures and a classical regularizer based on linear elastic deformation energy. It establishes conditions for the existence and uniqueness of solutions for both methods and presents synthetic experimental results comparing them with a standard method based on the sum of squared differences similarity measure. These methods have been tested to capture various non-affine deformations in images, both with and without noise, and their convergence rates have been analyzed. Furthermore, the effectiveness of these methods was also evaluated in a lung image registration scenario. |
| title | Methods based on Radon transform for non-affine deformable image registration of noisy images |
| topic | Computer Vision and Pattern Recognition Numerical Analysis Analysis of PDEs Optimization and Control |
| url | https://arxiv.org/abs/2409.00037 |