Please use this identifier to cite or link to this item:
|Title:||Integrative diffeomorphic metric mapping based on image and unlabeled points|
|Citation:||Du, J.,Qiu, A. (2011). Integrative diffeomorphic metric mapping based on image and unlabeled points. 2011 IEEE/ICME International Conference on Complex Medical Engineering, CME 2011 : 588-592. ScholarBank@NUS Repository. https://doi.org/10.1109/ICCME.2011.5876809|
|Abstract:||This paper introduces a variational problem under the setting of large deformation diffeomorphic metric mapping (LDDMM) for whole brain mapping when images and unlabeled points on sulcal and gyral curves are simultaneously carried from one subject to the other through a flow of diffeomorphisms. Its Euler-Lagrange equation is described in terms of momentum, a linear transformation of the velocity vector field of the diffeomorphic flow. The numerical implementation for solving this variational problem, which involves kernel application in an irregular grid, is made feasible by the introduction of a class of computationally friendly kernels. This algorithm is applied to register 40 magnetic resonance (MR) brain images. Our results show the alignment improvement in the cortical regions when compared with the intensity-based LDDMM. © 2011 IEEE.|
|Source Title:||2011 IEEE/ICME International Conference on Complex Medical Engineering, CME 2011|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Sep 29, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.