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) |
|---|---|
| Pages (from-to) | 505-512 |
| Number of pages | 8 |
| Journal | Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention |
| Volume | 17 |
| State | Published - Jan 1 2014 |
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ASJC Scopus subject areas
- Medicine(all)
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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.
In: Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, Vol. 17, 01.01.2014, p. 505-512.Research output: Contribution to journal › Article
TY - JOUR
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=84922289006&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84922289006&partnerID=8YFLogxK
M3 - Article
VL - 17
SP - 505
EP - 512
JO - Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
JF - Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
ER -