Skeleton-based abdominal aorta registration technique

Vascular diseases are the most challenging health problems in developed countries. The vascular segmentation as well as registration techniques are the topics of past and ongoing research activities. In this work we target an abdominal aorta registration technique. The developed methodology is useful in the assessment of abdominal aortic aneurysm treatment by visualizing the correspondence between pre- and postoperative Computed Tomography (CT) data. The presented approach makes it possible to match all voxels belonging to the aorta from different CT series. It is based on aorta lumen segmentation and graph matching method. To segment the lumen area a hybrid level-set active contour approach is used. The matching step is performed based on a path similarity skeleton graph matching procedure. The registration results have been tested on the database of 8 patients, for which two different contrast-enhanced CT series were acquired. All registration results achieved with our system and verified by an expert prove the efficiency of the approach and encourage to further develop this method.

[1]  L.-K. Shark,et al.  Medical Image Segmentation Using New Hybrid Level-Set Method , 2008, 2008 Fifth International Conference BioMedical Visualization: Information Visualization in Medical and Biomedical Informatics.

[2]  Zhengyan Sun Biomedical Imaging and Intervention Journal Helical Ct Angiography of Fenestrated Stent Grafting of Abdominal Aortic Aneurysms , 2022 .

[3]  Hari Sundar,et al.  An Efficient Graph-Based Deformable 2D/3D Registration Algorithm with Applications for Abdominal Aortic Aneurysm Interventions , 2010, MIAR.

[4]  Bo Ding,et al.  Visual check and automatic compensation for patient movement during image-guided Abdominal Aortic Aneurysm (AAA) stenting , 2012, 2012 5th International Conference on BioMedical Engineering and Informatics.

[5]  E. Pietka,et al.  Kernelized Fuzzy c-means Method in Fast Segmentation of Demyelination Plaques in Multiple Sclerosis , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[6]  S. Napel,et al.  An abdominal aortic aneurysm segmentation method: level set with region and statistical information. , 2006, Medical physics.

[7]  R. V. Van Uitert,et al.  Subvoxel precise skeletons of volumetric data based on fast marching methods. , 2007, Medical physics.

[8]  Rui Liao,et al.  Toward smart utilization of two X-ray images for 2-D/3-D registration applied to abdominal aortic aneurysm interventions , 2011, 2011 4th International Conference on Biomedical Engineering and Informatics (BMEI).

[9]  Qiang Wang,et al.  Optimal Subsequence Bijection , 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).

[10]  Rodney A. White,et al.  AneuRx stent graft versus open surgical repair of abdominal aortic aneurysms: multicenter prospective clinical trial. , 1999, Journal of vascular surgery.

[11]  Max A. Viergever,et al.  Active-shape-model-based segmentation of abdominal aortic aneurysms in CTA images , 2002, SPIE Medical Imaging.

[12]  Longin Jan Latecki,et al.  Path Similarity Skeleton Graph Matching , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[13]  Longin Jan Latecki,et al.  Maximum weight cliques with mutex constraints for video object segmentation , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[14]  Isabelle Bloch,et al.  A review of 3D vessel lumen segmentation techniques: Models, features and extraction schemes , 2009, Medical Image Anal..