Large deformation diffeomorphic metric mapping of vector fields
Year: 2005
Type: article
Abstract: In large-deformation diffeomorphic metric mapping (LDDMM), the diffeomorphic matching of images are modeled as evolution in time, or a flow, of an associated smooth velocity vector field v controlling the evolution. The initial momentum parameterizes the whole geodesic and encodes the shape and form of the target image. Thus, methods such as principal component analysis (PCA) of the initial momentum leads to analysis of anatomical shape and form in target images without being restricted to small-deformation assumption in the analysis of linear displacements. We apply this approach to a study of dementia of the Alzheimer type (DAT). The left hippocampus in the DAT group shows significant shape abnormality while the right hippocampus shows similar pattern of abnormality. Further, PCA of the initial momentum leads to correct classification of 12 out of 18 DAT subjects and 22 out of 26 control subjects.
Authors: Yan Cao, M.I. Miller, R.L. Winslow, L. Younes
Institution: Johns Hopkins University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: Human White Matter Tract Mapping by Diffusion MRI, Mapping Abnormal Neurodevelopment in Schizophrenia, Morphometric Analysis of the Superior Temporal Gyrus, Resource for Quantitative Functional MRI, Anatomical Remodeling and Electrical Conduction in Heart, Resource for Quantitative Functional FMRI, Stress, Glucocorticoids and Alzheimer Disease, Corticolimbic Degeneration and Treatment of Dementia, Alzheimer's Disease Research Center, Healthy Aging and Senile Dementia, Neuromorphometry in Schizophrenia by Computer Algorithm, REPAIR OF DAMAGED PROTEIN AND SURVIVAL OF AGING E COLI
OpenAlex ID: W2145138920
