Theme: Shape Analysis


 

Shape Analysis

The anatomical structures of interest that we study within the brain are complex and need to be characterized in a consistent, reliable manner. We at UCNIA are developing methods for representing and analyzing shapes from image data to facilitate the study of anatomical changes. This also includes the development of shape alignment procedures, spatial correspondence estimation, and statistical analysis of shape parameters.

The purpose is to characterize the neuroanatomical variations observed in neurological disorders such as dementia. We do global statistical analysis of brain anatomy and identify relevant shape deformation patterns that explain corresponding variations in clinical neuropsychological measures. The motivation is to model the inherent relation between anatomical shape and clinical measures and evaluate its statistical significance.

One of the primary goals of computational anatomy is the statistical analysis of anatomical variability in large populations of images.

 

theme-shape-analysis

 

LV1 log Jacobians overlayed on atlas. Red denotes regions of local expansion and blue denotes regions of local contraction

 

Publications:

  • E.B. Dam, P.T. Fletcher, S.M. Pizer. “Automatic shape model building based on principal geodesic analysis bootstrapping,” In Medical Image Analysis, Vol. 12, No. 2, Note: Epub Feb 2 2010, pp. 136--151. 2010.  PubMed ID: 18178124
  • N. Singh, P.T. Fletcher, J.S. Preston, L. Ha, R. King, J.S. Marron, M. Wiener, S. Joshi. “Multivariate Statistical Analysis of Deformation Momenta Relating Anatomical Shape to Neuropsychological Measures,” In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010, Lecture Notes in Computer Science (LCNS), Vol. 6363/2010, pp. 529-537. 2010.  PubMed ID: 20879441

  • B.C. Davis, P.T. Fletcher, E. Bullitt, S. Joshi. “Population Shape Regression from Random Design Data,” In International Journal of Computer Vision, Vol. 90, No. 1, Note: Marr Prize Special Issue, pp. 255--266. October, 2010.

Quick Links

 

Research Projects

 

PIs