Spatial normalization of spine MR images for statistical correlation of lesions with clinical symptoms.
An image analysis method was developed for spatial normalization of spine magnetic resonance images. A deformable shape model of the spine is first constructed, and it is subsequently used by an automated algorithm to find a shape transformation that places patient data into a stereotactic space. Very good agreement with manual segmentations was observed. The main application of this method is in lesion-deficit analysis for determining associations between structural damage and clinical symptoms.
Center for Biomedical Image Computing, Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 601 N Caroline St, JHOC3220, Baltimore, MD 21287, USA.
Christos
C
Davatzikos
Dengfeng
D
Liu
Dinggang
D
Shen
Edward H
EH
Herskovits
D000465:Algorithms; D004548:Elasticity; D006801:Humans; D017116:Low Back Pain / Q000175:diagnosis; D008279:Magnetic Resonance Imaging; D008953:Models, Anatomic; D013131:Spine / Q000033:anatomy & histology*
Non-programmatic