A transformation similarity constraint for groupwise nonlinear registration in longitudinal neuroimaging studies

Greg M. Fleishman; Boris A. Gutman; P. Thomas Fletcher; Paul Thompson

doi:10.1117/12.2080841

20 March 2015 A transformation similarity constraint for groupwise nonlinear registration in longitudinal neuroimaging studies

Greg M. Fleishman, Boris A. Gutman, P. Thomas Fletcher, Paul Thompson

Author Affiliations +

Proceedings Volume 9413, Medical Imaging 2015: Image Processing; 94130X (2015) https://doi.org/10.1117/12.2080841
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

Patients with Alzheimer's disease and other brain disorders often show a similar spatial distribution of volume change throughout the brain over time, but this information is not yet used in registration algorithms to refine the quantification of change. Here, we develop a mathematical basis to incorporate that prior information into a longitudinal structural neuroimaging study. We modify the canonical minimization problem for non-linear registration to include a term that couples a collection of registrations together to enforce group similarity. More specifically, throughout the computation we maintain a group-level representation of the transformations and constrain updates to individual transformations to be similar to this representation. The derivations necessary to produce the Euler-Lagrange equations for the coupling term are presented and a gradient descent algorithm based on the formulation was implemented. We demonstrate using 57 longitudinal image pairs from the Alzheimer's Disease Neuroimaging Initiative (ADNI) that longitudinal registration with such a groupwise coupling prior is more robust to noise in estimating change, suggesting such change maps may have several important applications.

Citation Download Citation

Greg M. Fleishman, Boris A. Gutman, P. Thomas Fletcher, and Paul Thompson "A transformation similarity constraint for groupwise nonlinear registration in longitudinal neuroimaging studies", Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 94130X (20 March 2015); https://doi.org/10.1117/12.2080841

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available