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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

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 languageEnglish (US)
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings
PublisherSpringer Verlag
Pages505-512
Number of pages8
EditionPART 2
ISBN (Print)9783319104690
DOIs
StatePublished - Jan 1 2014
Event17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - Boston, MA, United States
Duration: Sep 14 2014Sep 18 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume8674 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014
CountryUnited States
CityBoston, MA
Period9/14/149/18/14

Fingerprint

Constraint Programming
Integer programming
Integer Programming
Vessel
Angiography
Magnetic resonance
Tomography
Brain
Pruning
Corrosion
High Resolution
Micromagnetics
Magnetic Resonance
Computed Tomography
Experiments
Mouse
Connectivity
Bifurcation
Angle
Graph in graph theory

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Rempfler, M., Schneider, M., Ielacqua, G. D., Xiao, X., Stock, S. R., Klohs, J., ... 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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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 proceedingConference contribution

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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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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