Interactive volumetric segmentation through least-squares optimization of local hessian-constrained implicits

A great number of volumetric datasets have been routinely acquired everyday and their qualities are varying tremendously, without proper processing they could not be directly utilized. Specifically, volumetric segmentation plays a vital role in many downstream applications, including geometric modeling, scientific visualization, and medical diagnosis. So far, many volume segmentation methods have been proposed, Top et al. [2011] designed an interactive segmentation tool by interactively contouring on some sparse slices and Ijiri et al. [2013] developed a system to extract contours and evaluate the scalar field in spatial domain.