| Publikationstyp: | Konferenz: Paper |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | TGIF : topological gap in-fill for vascular networks |
| Autor/-in: | Schneider, Matthias Hirsch, Sven Weber, Bruno Székely, Gábor Menze, Bjoern H. |
| DOI: | 10.1007/978-3-319-10470-6_12 |
| Tagungsband: | Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 Part II |
| Seite(n): | 89 |
| Seiten bis: | 96 |
| Angaben zur Konferenz: | MICCAI, 17th International Conference, Boston, USA, 14-18 September 2014 |
| Erscheinungsdatum: | 2014 |
| Reihe: | Lecture Notes in Computer Science |
| Reihenzählung: | 8674 |
| Verlag / Hrsg. Institution: | Springer |
| Verlag / Hrsg. Institution: | Cham |
| ISBN: | 978-3-319-10469-0 978-3-319-10470-6 |
| ISSN: | 0302-9743 1611-3349 |
| Sprache: | Englisch |
| Fachgebiet (DDC): | 610: Medizin und Gesundheit |
| Zusammenfassung: | This paper describes a new approach for the reconstruction of complete 3-D arterial trees from partially incomplete image data. We utilize a physiologically motivated simulation framework to iteratively generate artificial, yet physiologically meaningful, vasculatures for the correction of vascular connectivity. The generative approach is guided by a simplified angiogenesis model, while at the same time topological and morphological evidence extracted from the image data is considered to form functionally adequate tree models. We evaluate the effectiveness of our method on four synthetic datasets using different metrics to assess topological and functional differences. Our experiments show that the proposed generative approach is superior to state-of-the-art approaches that only consider topology for vessel reconstruction and performs consistently well across different problem sizes and topologies. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/13618 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Departement: | Life Sciences und Facility Management |
| Organisationseinheit: | Institut für Computational Life Sciences (ICLS) |
| Enthalten in den Sammlungen: | Publikationen Life Sciences und Facility Management |
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Schneider, M., Hirsch, S., Weber, B., Székely, G., & Menze, B. H. (2014). TGIF : topological gap in-fill for vascular networks [Conference paper]. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 Part II, 89–96. https://doi.org/10.1007/978-3-319-10470-6_12
Schneider, M. et al. (2014) ‘TGIF : topological gap in-fill for vascular networks’, in Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 Part II. Cham: Springer, pp. 89–96. Available at: https://doi.org/10.1007/978-3-319-10470-6_12.
M. Schneider, S. Hirsch, B. Weber, G. Székely, and B. H. Menze, “TGIF : topological gap in-fill for vascular networks,” in Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 Part II, 2014, pp. 89–96. doi: 10.1007/978-3-319-10470-6_12.
SCHNEIDER, Matthias, Sven HIRSCH, Bruno WEBER, Gábor SZÉKELY und Bjoern H. MENZE, 2014. TGIF : topological gap in-fill for vascular networks. In: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 Part II. Conference paper. Cham: Springer. 2014. S. 89–96. ISBN 978-3-319-10469-0
Schneider, Matthias, Sven Hirsch, Bruno Weber, Gábor Székely, and Bjoern H. Menze. 2014. “TGIF : Topological Gap In-Fill for Vascular Networks.” Conference paper. In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 Part II, 89–96. Cham: Springer. https://doi.org/10.1007/978-3-319-10470-6_12.
Schneider, Matthias, et al. “TGIF : Topological Gap In-Fill for Vascular Networks.” Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 Part II, Springer, 2014, pp. 89–96, https://doi.org/10.1007/978-3-319-10470-6_12.
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