TY - GEN
T1 - Graph to graph matching
T2 - 24th International Symposium on Computer-Based Medical Systems, CBMS 2011
AU - Laura, Cristina Oyarzun
AU - Drechsler, Klaus
PY - 2011
Y1 - 2011
N2 - State of the art anatomical tree matching algorithms find correspondences between trees that contain topological differences. However there are still open problems that were not considered until now. For example, when the liver vas-culature is segmented, portal and hepatic vein are not separated due to segmentation errors. Because of this reason the resulting structure is not a tree but a graph. On the other hand, inaccuracies in the generation of the graph, as well as artifacts or inhomogeneities in the contrast medium result in graphs containing gaps. In this work, we present a novel graph to graph matching algorithm. It solves the aforementioned problems by taking the whole graph structure into account and does not depend on separated trees. In addition to this it is robust against gaps in the graph. We developed our algorithm so that it does not depend on the root of the graph which is often assumed to be known. The algorithm was evaluated on real clinical data of the liver.
AB - State of the art anatomical tree matching algorithms find correspondences between trees that contain topological differences. However there are still open problems that were not considered until now. For example, when the liver vas-culature is segmented, portal and hepatic vein are not separated due to segmentation errors. Because of this reason the resulting structure is not a tree but a graph. On the other hand, inaccuracies in the generation of the graph, as well as artifacts or inhomogeneities in the contrast medium result in graphs containing gaps. In this work, we present a novel graph to graph matching algorithm. It solves the aforementioned problems by taking the whole graph structure into account and does not depend on separated trees. In addition to this it is robust against gaps in the graph. We developed our algorithm so that it does not depend on the root of the graph which is often assumed to be known. The algorithm was evaluated on real clinical data of the liver.
UR - http://www.scopus.com/inward/record.url?scp=80053045993&partnerID=8YFLogxK
U2 - 10.1109/CBMS.2011.5999139
DO - 10.1109/CBMS.2011.5999139
M3 - Conference contribution
AN - SCOPUS:80053045993
SN - 9781457711909
T3 - Proceedings - IEEE Symposium on Computer-Based Medical Systems
BT - Proceedings of the 24th International Symposium on Computer-Based Medical Systems, CBMS 2011
Y2 - 27 June 2011 through 30 June 2011
ER -