An efficient, scalable, and adaptable framework for solving generic systems of level-set PDEs.

ABSTRACT: In the last decade, level-set methods have been actively developed for applications in image registration, segmentation, tracking, and reconstruction. However, the development of a wide variety of level-set PDEs and their numerical discretization schemes, coupled with hybrid combinations of PDE terms, stopping criteria, and reinitialization strategies, has created a software logistics problem. In the absence of an integrative design, current toolkits support only specific types of level-set implementations which restrict future algorithm development since extensions require significant code duplication and effort. In the new NIH/NLM Insight Toolkit (ITK) v4 architecture, we implemented a level-set software design that is flexible to different numerical (continuous, discrete, and sparse) an

SUBMITTER: Mosaliganti KR 

PROVIDER: S-EPMC3872740 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature