2024/08/18 by Daniel E. Hurtado, Hurtado, Daniel E., Axel Osses +3
Computer Science · #Analysis of PDEs (math.AP) #Computer Vision and Pattern Recognition (cs.CV) #Digital Image Processing Techniques #FOS: Computer and information sciences #FOS: Mathematics #Image and Object Detection Techniques #Medical Image Segmentation Techniques #Numerical Analysis (math.NA) #Optimization and Control (math.OC)
paper · pdf · doi:10.48550/arxiv.2409.00037
openalex publication_date 2024/08/18 · openalex created_date 2024/09/29 · openalex updated_date 2026/08/02
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.