Publication type: Conference paper
Type of review: Peer review (publication)
Title: TGIF : topological gap in-fill for vascular networks
Authors: Schneider, Matthias
Hirsch, Sven
Weber, Bruno
Székely, Gábor
Menze, Bjoern H.
DOI: 10.1007/978-3-319-10470-6_12
Proceedings: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 Part II
Page(s): 89
Pages to: 96
Conference details: MICCAI, 17th International Conference, Boston, USA, 14-18 September 2014
Issue Date: 2014
Series: Lecture Notes in Computer Science
Series volume: 8674
Publisher / Ed. Institution: Springer
Publisher / Ed. Institution: Cham
ISBN: 978-3-319-10469-0
978-3-319-10470-6
ISSN: 0302-9743
1611-3349
Language: English
Subject (DDC): 610: Medicine and health
Abstract: 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
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: Life Sciences and Facility Management
Organisational Unit: Institute of Computational Life Sciences (ICLS)
Appears in collections:Publikationen Life Sciences und Facility Management

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