Authors:
Nefeli Lamprinou
;
Nikolaos Nikolikos
and
Emmanouil Z. Psarakis
Affiliation:
Computer Engineering and Informatics Department, Patras, Greece
Keyword(s):
Groupwise Registration, Congealign, Image Alignment, Medical Imaging, Multi-modal Alignment, Self Quotient Image.
Abstract:
Compared with pairwise registration, groupwise registration is capable of handling a large-scale population of images simultaneously in an unbiased way. In this work we improve upon the state-of-the-art pixel-level, Least-Squares (LS) based groupwise image registration methods. Specifically, we propose a new iterative algorithm which outperforms in terms of its computational cost, a recently introduced LS based iterative congealing scheme. Namely, the particle system that was introduced in that work is used and by imposing its “center of mass” to be motionless, during each iteration of the minimization process, a sequence of “centroid” images whose limit is the unknown “mean” image is optimally in closed form defined, thus solving in a reduced computational cost the groupwise problem. Moreover, the registration technique is properly adapted by the use of Self Quotient Images (SQI) in order to become capable for solving the groupwise registration of multimodal images. Since the propos
ed congealing technique is invariant to the size of the image set, it can be used for the successful solution of the problem on large image sets with low complexity. From the application of the proposed technique on a series of experiments for the groupwise registration of face, unimodal and multimodal magnetic resonance image sets its performance seems to be very good.
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