A novel method for simultaneous segmentation of multiple interacting surfaces belonging to
multiple interacting objects, called LOGISMOS (layered optimal graph image segmentation
of multiple objects and surfaces), is reported. The approach is based on the algorithmic
incorporation of multiple spatial inter-relationships in a single n-dimensional graph, followed
by graph optimization that yields a globally optimal solution. The LOGISMOS method's utility
and performance are demonstrated on a bone and cartilage segmentation task in the human …

<? Pub Dtl=""?> Automated reconstruction of the cortical surface is one of the most
challenging problems in the analysis of human brain magnetic resonance imaging (MRI). A
desirable segmentation must be both spatially and topologically accurate, as well as robust
and computationally efficient. We propose a novel algorithm, LOGISMOS-B, based on
probabilistic tissue classification, generalized gradient vector flows and the LOGISMOS
graph segmentation framework. Quantitative results on MRI datasets from both healthy …