1 research outputs found
Edge Preserving Multi-Modal Registration Based On Gradient Intensity Self-Similarity
Image registration is a challenging task in the world of medical imaging.
Particularly, accurate edge registration plays a central role in a variety of
clinical conditions. The Modality Independent Neighbourhood Descriptor (MIND)
demonstrates state of the art alignment, based on the image self-similarity.
However, this method appears to be less accurate regarding edge registration.
In this work, we propose a new registration method, incorporating gradient
intensity and MIND self-similarity metric. Experimental results show the
superiority of this method in edge registration tasks, while preserving the
original MIND performance for other image features and textures