A survey of image registration techniques
ACM Computing Surveys (CSUR)
Alignment by maximization of mutual information
Alignment by maximization of mutual information
Intensity based image registration by minimizing exponential function weighted residual complexity
Computers in Biology and Medicine
A Gauss-Newton approach to joint image registration and intensity correction
Computer Methods and Programs in Biomedicine
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We present a novel approach for a combined homogenization and registration technique. Medical image data is often disturbed by inhomogeneities from staining, illumination or attenuation. State-of-the-art approaches tackle homogenization and registration separately. Our new method attacks both troublemakers simultaneously. It is modeled as a minimization problem of a functional consisting of a distance measure and regularizers for the displacement field and the grayscale correction term. The simultaneous homogenization and registration enables an automatic correction of gray values and improves the local contrast. The combined approach takes slightly more computing time for an optimization step as compared to the non-combined scheme and so is much faster than sequential methods. We tested the performance both on academic and real life data. It turned out, that the combined approach enhances image quality, especially the visibility of slightly differentiable structures.