Title :
Deformation invariant attribute vector for 3D image registration: method and validation
Author :
Li, Gang ; Liu, Tianming ; Young, Geoffrey ; Guo, Lei ; Wong, Stephen T C
Author_Institution :
Sch. of Autom., Northwestern Polytech. Univ., Xi´´an
Abstract :
This paper proposes a novel method to define deformation invariant attribute vector for each voxel in 3D image for the purpose of anatomic correspondence detection. This is the extension of the work for 2D deformation invariant attribute using geodesic intensity histogram (GIH). Our original contribution is to extend this 2D technique to 3D image, and validate the method using synthesized deformation in 3D brain MRI image. Both theoretic analysis and initial validation result show that the proposed attribute vector is invariant to deformation. This deformation invariant attribute vector has wide applications in registration of 3D medical images
Keywords :
biomedical MRI; brain; image registration; medical image processing; 3D brain MRI image; 3D image registration; anatomic correspondence detection; deformation invariant attribute vector; geodesic intensity histogram; Application software; Biomedical imaging; Computer vision; Histograms; Image matching; Image registration; Jacobian matrices; Magnetic resonance imaging; Medical diagnostic imaging; Surface morphology;
Conference_Titel :
Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-9576-X
DOI :
10.1109/ISBI.2006.1624948