Graph based methods have been used for medical image segmentation problems. Each pixel (voxel in 3D) in the image is represented by a node in the graph while edges connect neighboring nodes. In addition, two nodes namely source and sink are added. A cost is defined for each node (except source and sink) based on which a minimum cost closed set is computed. This set corresponds to a boundary (surface in 3D) which separates nodes belonging to the source from those belonging to the sink. Usually this boundary gives the segmentation required. Details are in this paper.
I have seen quite a few works using this approach but some call their method graph search (Garvin et al.) while others call theirs graph cut (Kaba et al). Upon reading, these works appear very similar.
There is another work which implies a difference between graph search and graph cut but even after reading this work, I am unable to understand the difference.
Can someone please clarify the difference, if any?