naa a22 4500 510808263 CHVBK 20180411083428.0 cr unu---uuuuu 180411e20130301xx s 000 0 eng 10.1007/s11548-012-0784-4 doi (NATIONALLICENCE)springer-10.1007/s11548-012-0784-4 Three-dimensional skeletonization and symbolic description in vascular imaging: preliminary results [Elektronische Daten] [L. Verscheure, L. Peyrodie, A. Dewalle, N. Reyns, N. Betrouni, S. Mordon, M. Vermandel] Objective: A general method was developed to analyze and describe tree-like structures needed for evaluation of complex morphology, such as the cerebral vascular tree. Clinical application of the method in neurosurgery includes planning of the surgeon's intraoperative gestures. Method: We have developed a 3D skeletonization method adapted to tubular forms with symbolic description. This approach implements an iterative Dijkstra minimum cost spanning tree, allowing a branch-by-branch skeleton extraction. The proposed method was implemented using the laboratory software platform (ArtiMed). The 3D skeleton approach was tested on simulated data and preliminary trials on clinical datasets mainly based on magnetic resonance image acquisitions. Results: A specific experimental evaluation plan was designed to test the skeletonization and symbolic description methods. Accuracy was tested by calculating the positioning error, and robustness was verified by comparing the results on a series of 18 rotations of the initial volume. Accuracy evaluation showed a Haussdorff's distance always smaller than 17 voxels and Dice's similarity coefficient greater than 70%. Conclusion: Our method of symbolic description enables the analysis and interpretation of a vascular network obtained from angiographic images. The method provides a simplified representation of the network in the form of a skeleton, as well as a description of the corresponding information in a tree-like view. CARS, 2012 Medical imaging nationallicence Vascular network nationallicence Angiography nationallicence 3D skeletonization nationallicence Symbolic description nationallicence Verscheure L. Inserm U703, Université Lille 2, 59120, CHRU Lille, Loos, France aut Peyrodie L. PRES Université Lille Nord de France, Lille, France aut Dewalle A. Inserm U703, Université Lille 2, 59120, CHRU Lille, Loos, France aut Reyns N. Inserm U703, Université Lille 2, 59120, CHRU Lille, Loos, France aut Betrouni N. Inserm U703, Université Lille 2, 59120, CHRU Lille, Loos, France aut Mordon S. Inserm U703, Université Lille 2, 59120, CHRU Lille, Loos, France aut Vermandel M. Inserm U703, Université Lille 2, 59120, CHRU Lille, Loos, France aut International Journal of Computer Assisted Radiology and Surgery Springer-Verlag 8/2(2013-03-01), 233-246 1861-6410 8:2<233 2013 8 11548 https://doi.org/10.1007/s11548-012-0784-4 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11548-012-0784-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Verscheure L. Inserm U703, Université Lille 2, 59120, CHRU Lille, Loos, France aut NATIONALLICENCE 700 1- Peyrodie L. PRES Université Lille Nord de France, Lille, France aut NATIONALLICENCE 700 1- Dewalle A. Inserm U703, Université Lille 2, 59120, CHRU Lille, Loos, France aut NATIONALLICENCE 700 1- Reyns N. Inserm U703, Université Lille 2, 59120, CHRU Lille, Loos, France aut NATIONALLICENCE 700 1- Betrouni N. Inserm U703, Université Lille 2, 59120, CHRU Lille, Loos, France aut NATIONALLICENCE 700 1- Mordon S. Inserm U703, Université Lille 2, 59120, CHRU Lille, Loos, France aut NATIONALLICENCE 700 1- Vermandel M. Inserm U703, Université Lille 2, 59120, CHRU Lille, Loos, France aut NATIONALLICENCE 773 0- International Journal of Computer Assisted Radiology and Surgery Springer-Verlag 8/2(2013-03-01), 233-246 1861-6410 8:2<233 2013 8 11548 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer