Meeting Banner
Abstract #3506

An algorithm and quantitative evaluation framework for registration of multi-modal brain MRI

Omar Ocegueda 1 , Eleftherios Garyfallidis 2 , Maxime Descoteaux 2 , and Mariano Rivera 1

1 Computer Science Department, Centro de Investigacin en Matemticas, Guanajuato, Guanajuato, Mexico, 2 Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science department, Universit de Sherbrooke, Sherbrooke, Qubec, Canada

We present a new algorithm for multi-modal symmetric diffeomorphic image registration and propose a validation protocol, based on existing manually annotated datasets, to quantitatively evaluate multi-modal image registration algorithms. Our validation protocol reveals that the Cross Correlation (CC) metric may be severely affected in the multi-modal case even though it has proven to be one of the most robust and accurate metrics for mono-modal registration. Our algorithm is based on the Symmetric Normalization (SyN) algorithm. It compares favourably with SyN with CC (in the multi-modal case) and is very competitive with SyN with Mutual Information.

This abstract and the presentation materials are available to members only; a login is required.

Join Here