A label fusion method using conditional random fields with higher-order potentials: Application to hippocampal segmentation

Conclusions We introduce a new label fusion method based on a CRF model and on ROIs. The CRF model is characterized by a pseudo-Boolean function defined on unary, pairwise and higher-order potentials. The proposed Boolean function is representable by graphs. A globally optimal binary labeling is found using a st-mincut algorithm in each ROI. We show that the proposed approach is very competitive with respect to recently reported methods. Graphical abstract Highlights
Source: Artificial Intelligence in Medicine - Category: Bioinformatics Source Type: research