• Aucun résultat trouvé

Joint T1 and Brain Fiber Log-Demons Registration Using Currents to Model Geometry

N/A
N/A
Protected

Academic year: 2021

Partager "Joint T1 and Brain Fiber Log-Demons Registration Using Currents to Model Geometry"

Copied!
10
0
0

Texte intégral

Figure

Fig. 1. Influence of γ. Similarity measure average of the 5 training set permutations with varying γ
Fig. 2. Comparison of SLDD, STD, Ants and LGD Top: Target fibers over- over-lapped with registered fibers from an arbitrary chosen registration

Références

Documents relatifs

These indicators are, however, unable to indicate the outdoor view (connection to outdoor), indoor view (feeling of privacy), luminance (leading to discomfort glare), and

screened by wall and ceiling surfaces. For separation between service spaces, the NBCC has no STC requirement. The SMACNA Technical Paper on Improper Fire Damper Installation [10-3]

Automatic change detection in longitudinal brain MRI clas- sically consists in a sequential pipeline where registration is estimated as a pre-processing step before detecting

The direct feature matching technique described ear- lier is able to capture very large deformations, but is however not able to guarantee a diffeomorphic transfor- mation.

On the other hand, in [13] the authors proposed an efficient diffeomorphic registration scheme based on the demons algorithm that encodes the optimization steps, but not the

We presented in this chapter a method to extract reliable differential geometry features (crest lines and extremal points) from 3D images and several rigid registration al- gorithms

• Laplacian comparison theorems for the canonical sub-Laplacian (Theorem 7); • Formulas for the sub-Riemannian curvature of 3-Sasakian manifolds (Theorem 8); • Sharp bounds for

réponse cellulaire antivirale : il montre que si lors de l’infection virale la RNase L clive aussi les ARN cellulaires, ce qui était connu, cette activité n’est pas