Extracting vascular networks under physiological constraints via integer programming

Markus Rempfler; Matthias Schneider; Giovanna D. Ielacqua; Xianghui Xiao; Stuart R. Stock; Jan Klohs; Gábor Székely; Bjoern Andres; Bjoern H. Menze

doi:10.1007/978-3-319-10470-6_63

Extracting vascular networks under physiological constraints via integer programming

Markus Rempfler, Matthias Schneider, Giovanna D. Ielacqua, Xianghui Xiao, Stuart R. Stock, Jan Klohs, Gábor Székely, Bjoern Andres, Bjoern H. Menze

Cell & Developmental Biology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Scopus citations

Abstract

We introduce an integer programming-based approach to vessel network extraction that enforces global physiological constraints on the vessel structure and learn this prior from a high-resolution reference network. The method accounts for both image evidence and geometric relationships between vessels by formulating and solving an integer programming problem. Starting from an over-connected network, it is pruning vessel stumps and spurious connections by evaluating bifurcation angle and connectivity of the graph. We utilize a high-resolution micro computed tomography (μCT) dataset of a cerebrovascular corrosion cast to obtain a reference network, perform experiments on micro magnetic resonance angiography(μMRA) images of mouse brains and discuss properties of the networks obtained under different tracking and pruning approaches.

Original language	English (US)
Title of host publication	Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings
Publisher	Springer Verlag
Pages	505-512
Number of pages	8
Edition	PART 2
ISBN (Print)	9783319104690
DOIs	https://doi.org/10.1007/978-3-319-10470-6_63
State	Published - 2014
Event	17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - Boston, MA, United States Duration: Sep 14 2014 → Sep 18 2014

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	8674 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014
Country	United States
City	Boston, MA
Period	9/14/14 → 9/18/14

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-319-10470-6_63

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Rempfler, M., Schneider, M., Ielacqua, G. D., Xiao, X., Stock, S. R., Klohs, J., Székely, G., Andres, B., & Menze, B. H. (2014). Extracting vascular networks under physiological constraints via integer programming. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings (PART 2 ed., pp. 505-512). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8674 LNCS, No. PART 2). Springer Verlag. https://doi.org/10.1007/978-3-319-10470-6_63

Rempfler, Markus ; Schneider, Matthias ; Ielacqua, Giovanna D. ; Xiao, Xianghui ; Stock, Stuart R. ; Klohs, Jan ; Székely, Gábor ; Andres, Bjoern ; Menze, Bjoern H. / Extracting vascular networks under physiological constraints via integer programming. Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings. PART 2. ed. Springer Verlag, 2014. pp. 505-512 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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abstract = "We introduce an integer programming-based approach to vessel network extraction that enforces global physiological constraints on the vessel structure and learn this prior from a high-resolution reference network. The method accounts for both image evidence and geometric relationships between vessels by formulating and solving an integer programming problem. Starting from an over-connected network, it is pruning vessel stumps and spurious connections by evaluating bifurcation angle and connectivity of the graph. We utilize a high-resolution micro computed tomography (μCT) dataset of a cerebrovascular corrosion cast to obtain a reference network, perform experiments on micro magnetic resonance angiography(μMRA) images of mouse brains and discuss properties of the networks obtained under different tracking and pruning approaches.",

author = "Markus Rempfler and Matthias Schneider and Ielacqua, {Giovanna D.} and Xianghui Xiao and Stock, {Stuart R.} and Jan Klohs and G{\'a}bor Sz{\'e}kely and Bjoern Andres and Menze, {Bjoern H.}",

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Rempfler, M, Schneider, M, Ielacqua, GD, Xiao, X, Stock, SR, Klohs, J, Székely, G, Andres, B & Menze, BH 2014, Extracting vascular networks under physiological constraints via integer programming. in Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 8674 LNCS, Springer Verlag, pp. 505-512, 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014, Boston, MA, United States, 9/14/14. https://doi.org/10.1007/978-3-319-10470-6_63

Extracting vascular networks under physiological constraints via integer programming. / Rempfler, Markus; Schneider, Matthias; Ielacqua, Giovanna D.; Xiao, Xianghui; Stock, Stuart R.; Klohs, Jan; Székely, Gábor; Andres, Bjoern; Menze, Bjoern H.

Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings. PART 2. ed. Springer Verlag, 2014. p. 505-512 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8674 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Rempfler, Markus

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AU - Klohs, Jan

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AB - We introduce an integer programming-based approach to vessel network extraction that enforces global physiological constraints on the vessel structure and learn this prior from a high-resolution reference network. The method accounts for both image evidence and geometric relationships between vessels by formulating and solving an integer programming problem. Starting from an over-connected network, it is pruning vessel stumps and spurious connections by evaluating bifurcation angle and connectivity of the graph. We utilize a high-resolution micro computed tomography (μCT) dataset of a cerebrovascular corrosion cast to obtain a reference network, perform experiments on micro magnetic resonance angiography(μMRA) images of mouse brains and discuss properties of the networks obtained under different tracking and pruning approaches.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Rempfler M, Schneider M, Ielacqua GD, Xiao X, Stock SR, Klohs J et al. Extracting vascular networks under physiological constraints via integer programming. In Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings. PART 2 ed. Springer Verlag. 2014. p. 505-512. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). https://doi.org/10.1007/978-3-319-10470-6_63