Task-optimal registration cost functions

Citation:

Yeo TBT, Sabuncu M, Golland P, Fischl B. Task-optimal registration cost functions. Med Image Comput Comput Assist Interv. 2009;12 (Pt 1) :598-606.

Date Published:

2009

Abstract:

In this paper, we propose a framework for learning the parameters of registration cost functions--such as the tradeoff between the regularization and image similiarity term--with respect to a specific task. Assuming the existence of labeled training data, we specialize the framework for the task of localizing hidden labels via image registration. We learn the parameters of the weighted sum of squared differences (wSSD) image similarity term that are optimal for the localization of Brodmann areas (BAs) in a new subject based on cortical geometry. We demonstrate state-of-the-art localization of V1, V2, BA44 and BA45.
Last updated on 01/24/2017