A framework for analysis of brain cine MR sequences
In this paper, we propose a framework to automate the assessment of the movements of a third cerebral ventricle in a cine MR sequence. Indeed, the goal of this assessment is to build an atlas of the movements of the healthy ventricles in the context of the hydrocephalus pathology. This approach is composed of two phases: a contour extraction, using fractional integration and a registration method, based on dynamic evolutionary optimization. The first phase of the framework is based on the fractional integration thresholding, that allows delineating the contours of the area of interest. In order to track over time each point of the primitive and achieve the assessment of the deformation, a matching method, based on a new dynamic optimization algorithm, called Dynamic Covariance Matrix Adaptation Evolution Strategy (D-CMAES), is used. The obtained results for quantification have been clinically validated by an expert and compared to those presented in the literature.
dynamic optimization image registration image segmentation fractional differentiation deformation model evolutionary algorithm