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 | |
| State | Published - Jan 1 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 |
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ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
Cite this
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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
TY - GEN
T1 - Extracting vascular networks under physiological constraints via integer programming
AU - Rempfler, Markus
AU - Schneider, Matthias
AU - Ielacqua, Giovanna D.
AU - Xiao, Xianghui
AU - Stock, Stuart R
AU - Klohs, Jan
AU - Székely, Gábor
AU - Andres, Bjoern
AU - Menze, Bjoern H.
PY - 2014/1/1
Y1 - 2014/1/1
N2 - 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.
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.
UR - http://www.scopus.com/inward/record.url?scp=84906987270&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84906987270&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-10470-6_63
DO - 10.1007/978-3-319-10470-6_63
M3 - Conference contribution
SN - 9783319104690
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 505
EP - 512
BT - Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings
PB - Springer Verlag
ER -