title: Insight into efficient image registration techniques and the demons algorithm.
abstract: As image registration becomes more and more central to many biomedical imaging applications, the efficiency of the algorithms becomes a key issue. Image registration is classically performed by optimizing a similarity criterion over a given spatial transformation space. Even if this problem is considered as almost solved for linear registration, we show in this paper that some tools that have recently been developed in the field of vision-based robot control can outperform classical solutions. The adequacy of these tools for linear image registration leads us to revisit non-linear registration and allows us to provide interesting theoretical roots to the different variants of Thirion's demons algorithm. This analysis predicts a theoretical advantage to the symmetric forces variant of the demons algorithm. We show that, on controlled experiments, this advantage is confirmed, and yields a faster convergence.
authors.affiliation: Asclepios Research Group, INRIA Sophia-Antipolis, France.
authors.forename: Tom
authors.initials: T
authors.lastname: Vercauteren
authors.forename: Xavier
authors.initials: X
authors.lastname: Pennec
authors.forename: Ezio
authors.initials: E
authors.lastname: Malis
authors.forename: Aymeric
authors.initials: A
authors.lastname: Perchant
authors.forename: Nicholas
authors.initials: N
authors.lastname: Ayache
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D003106:Colon / Q000166:cytology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D018613:Microscopy, Confocal / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique