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.
@article{arxiv.2409.00037,
title = {Methods based on Radon transform for non-affine deformable image registration of noisy images},
author = {Daniel E. Hurtado and Axel Osses and Rodrigo Quezada},
journal= {arXiv preprint arXiv:2409.00037},
year = {2024}
}