Measuring brain variability via sulcal lines registration: a diffeomorphic approach.
In this paper we present a new way of measuring brain variability based on the registration of sulcal lines sets in the large deformation framework. Lines are modelled geometrically as currents, avoiding then matchings based on point correspondences. At the end we retrieve a globally consistent deformation of the underlying brain space that best matches the lines. Thanks to this framework the measured variability is defined everywhere whereas a previous method introduced by P. Fillard requires tensors extrapolation. Evaluating both methods on the same database, we show that our new approach enables to describe different details of the variability and to highlight the major trends of deformation in the database thanks to a Tangent-PCA analysis.
Durrleman
Stanley
S
INRIA - Asclepios Research Project, Sophia Antipolis, France.
Pennec
Xavier
X
Trouvé
Alain
A
Ayache
Nicholas
N
D000465:Algorithms; D001185:Artificial Intelligence; D002540:Cerebral Cortex / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique