MATLAB PROJECT
Fast and Robust
Symmetric Image Registration Based on Distances Combining Intensity and Spatial
Information
Abstract:
Intensity-based image registration approaches rely on similarity
measures to guide the search for geometric correspondences with the high
affinity between images. The properties of the used measures are vital for the
robustness and accuracy of the registration. In this paper, a symmetric,
intensity interpolation-free, affine registration framework based on a
combination of intensity and spatial information is proposed. The excellent
performance of the framework is demonstrated on a combination of synthetic
tests, recovering known transformations in the presence of noise, and real
applications in biomedical and medical image registration, for both 2D and 3D
images. The method exhibits greater robustness and higher accuracy than
similarity measures in common use, when inserted into a standard gradient-based
registration framework available as part of the open source Insight
Segmentation and Registration Toolkit. The method is also empirically shown to
have a low computational cost, making it practical for real applications. The
source code is available.
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