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 (FCÄ) of the initial momentum leads to analysis of anatomical shape and form in target images without being restricted to smalldeformation 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.
Original language | English (US) |
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Pages (from-to) | 462-470 |
Number of pages | 9 |
Journal | IEEE Transactions on Medical Imaging |
Volume | 26 |
Issue number | 4 |
DOIs | |
State | Published - Apr 2007 |
Funding
Manuscript received September 19, 2006; revised October 13, 2006. This work was supported in part by the National Institutes of Health (NIH) under Grant P50-MH71616, Grant R01-MH60883, Grant R01-MH56584, Grant R01-MH064838, Grant P01-AG03991, Grant R01-AG025824, and P50-AG05681, AG05684, in part by the National Center for Research Resources under Grant P41-RR15241, in part by the National Science Foundation under Grant DMS-0456253, in part by the Natural Sciences and Engineering Research Council (Canada) under Grant 31-611387, and in part by a grant from the HIGHQ Foundation (Canada). Asterisk indicates corresponding author. *L. Wang is with the Department of Psychiatry, Washington University School of Medicine, Campus Box 8134, 660 S. Euclid Ave, St. Louis, MO 63110 USA (e-mail: [email protected]).
Keywords
- Alzheimer's disease
- Geodesic
- LDDMM
- Momentum
- PCA
ASJC Scopus subject areas
- Software
- Radiological and Ultrasound Technology
- Electrical and Electronic Engineering
- Computer Science Applications