Segmentation of multidimensional cardiac images.

One of the initial steps in the analysis of three-dimensional (3D)/four-dimensional (4D) images is Segmentation, which entails partitioning the images into relevant subsets such as object and background. In this paper, we present a multidimensional segmentation algorithm to extract object surfaces from Multidimensional Cardiac Computed Tomography (CT) scans. We propose the Generalized Morphological operators for segmentation in multidimensions. A priori knowledge of the approximate location of the object surface is communicated to the algorithm via the definition of the Search Space. The algorithm uses this definition of the Search Space to obtain the Surface Candidate elements. The search space specification reduces the computational cost and increases the reliability of the detected features.