LCClogDemons is an accurate and robust diffeomorphic registration framework based on the log-Demons.
It implements the symmetric Local Correlation Coefficient (LCC) as a similarity measure, and thus it is unbiased with respect to local linear intensity bias of the images.

LCClogDemons is suited for both inter and intra-subject registration, and compares well with respect to state-of-art methods. Thanks to the stable and consistent scheme for the computation of the Jacobian determinant of the transformation, LCClogDemons represents a reliable instrument for Tensor Based Morphometry (TBM).

The average registration time for typical 3D images is around 30 minutes for a single core on a Xeon platform 2.66Ghz quad core, 4Gb RAM.

Novelty of the V1.1: LCClogDemons implements the penalisation of the similarity term via a confidence mask.

LCC-Demons: a robust and accurate diffeomorphic registration algorithm.
Marco Lorenzi, Nicholas Ayache, Giovanni B Frisoni and Xavier Pennec.
NeuroImage 2013 (to appear, date of acceptance 27 Apr 2013)

The code is now available!

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