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Jan Hendrik Metzen, Tim Kröger, Andrea Schenk, Stephan Zidowitz, Heinz-Otto Peitgen, and Xiaoyi Jiang. Matching of anatomical tree structures for registration of medical images. Image and Vision Computing, 27(7):923–933, June 2009.
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Many medical applications require a registration of different images of the same organ. In many cases, such a registration is accomplished by manual placement of landmarks in the images. In this paper we propose a method which is able to find reasonable landmarks automatically. To achieve this, bifurcations of the vessel systems, which have been extracted from the images by a segmentation algorithm, are assigned by the so-called association graph method and the coordinates of these matched bifurcations can be used as landmarks for a non-rigid registration algorithm. Several constraints to be used in combination with the association graph method are proposed and evaluated on a ground truth consisting of anatomical trees from liver and lung. Furthermore, a method for preprocessing (tree pruning) as well as for postprocessing (clique augmentation) are proposed and evaluated on this ground truth. The proposed method achieves promising results for anatomical trees of liver and lung and for medical images obtained with different modalities and at different points in time.
@article{Metzen:IVC:2009,
title = {Matching of anatomical tree structures for registration of medical images},
volume = {27},
issn = {0262-8856},
url = {http://dx.doi.org/10.1016/j.imavis.2008.04.002},
doi = {10.1016/j.imavis.2008.04.002},
number = {7},
journal = {Image and Vision Computing},
author = {Jan Hendrik Metzen and Tim Kr\"{o}ger and Andrea Schenk and Stephan Zidowitz and {Heinz-Otto} Peitgen and Xiaoyi Jiang},
month = jun,
year = {2009},
pages = {923--933},
abstract = {Many medical applications require a registration of different images of the same organ. In many cases, such a registration is accomplished by manual placement of landmarks in the images. In this paper we propose a method which is able to find reasonable landmarks automatically. To achieve this, bifurcations of the vessel systems, which have been extracted from the images by a segmentation algorithm, are assigned by the so-called association graph method and the coordinates of these matched bifurcations can be used as landmarks for a non-rigid registration algorithm. Several constraints to be used in combination with the association graph method are proposed and evaluated on a ground truth consisting of anatomical trees from liver and lung. Furthermore, a method for preprocessing (tree pruning) as well as for postprocessing (clique augmentation) are proposed and evaluated on this ground truth. The proposed method achieves promising results for anatomical trees of liver and lung and for medical images obtained with different modalities and at different points in time.},
bib2html_pubtype = {Journal},
bib2html_rescat = {Graph Matching}
}
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