In this article we study the problem of thoracic image registration, in particular the estimation of complex anatomical deformations associated with the breathing cycle. Using the intimate link between the Riemannian geometry of the space of diffeomorphisms and the space of densities, we develop an image registration framework that incorporates both the fundamental law of conservation of mass as well as spatially varying tissue compressibility properties. By exploiting the geometrical structure, the resulting algorithm is computationally efficient, yet widely general.
@article{arxiv.1508.02543,
title = {Weighted Diffeomorphic Density Matching with Applications to Thoracic Image Registration},
author = {Caleb Rottman and Martin Bauer and Klas Modin and Sarang Joshi},
journal= {arXiv preprint arXiv:1508.02543},
year = {2018}
}
Comments
Accepted in Proceedings of the 5th MICCAI workshop on Mathematical Foundations of Computational Anatomy, Munich, Germany, 2015 (http://www-sop.inria.fr/asclepios/events/MFCA15/)