Simultaneous geometric - Iconic registration

Aristeidis Sotiras, Yangming Ou, Ben Glocker, Christos Davatzikos, Nikos Paragios

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

26 Scopus citations


In this paper, we introduce a novel approach to bridge the gap between the landmark-based and the iconic-based voxel-wise registration methods. The registration problem is formulated with the use of Markov Random Field theory resulting in a discrete objective function consisting of thee parts. The first part of the energy accounts for the iconic-based volumetric registration problem while the second one for establishing geometrically meaningful correspondences by optimizing over a set of automatically generated mutually salient candidate pairs of points. The last part of the energy penalizes locally the difference between the dense deformation field due to the iconic-based registration and the implied displacements due to the obtained correspondences. Promising results in real MR brain data demonstrate the potentials of our approach.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings
PublisherSpringer Verlag
Number of pages8
EditionPART 2
ISBN (Print)3642157440, 9783642157448
StatePublished - 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6362 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


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