3D/2D image registration by image transformation descriptors (ITDs) for thoracic aorta imaging

In this article, we present a novel image registration technique. Unlike most state of the art methods, our approach allows us to compute directly the relationship between images. The proposed registration framework, built in a modular way, can be adjusted to particular problems. Tests on sample image database of thoracic aorta proved that our method is fast and robust and could be successfully used for many cases. We have enhanced our previous works to provide a rapid 3D/2D registration method. It uses direct computing of the image transformation descriptors (ITDs) to align the projection images. The 3D transformation is estimated by an interesting technique which allows to propose a 3D pose update, interpreting the 2D transform of the projections in the 3D domain. The presented 3D/2D registration technique based on ITDs can be used as an initialization technique for classic registration algorithms. Its unique properties can be advantageous for many image alignment problems. The possibility of using different descriptors, adapted for particular cases, makes our approach very flexible. Fast time of computing is an important feature and motivates to use our technique even as an initialization step before execution of well known standard algorithms which could be more precise, but slow and sensitive to initialization of the parameters.