Name
Abstract | ||
|---|---|---|
Simulation of arterial stenting procedures prior to intervention allows for appropriate device selection as well as highlights potential complications. To this end, we present a framework for facilitating virtual aortic stenting from a contrast computer tomography (CT) scan. More specifically, we present a method for both lumen and outer wall segmentation that may be employed in determining both the appropriateness of intervention as well as the selection and localization of the device. The more challenging recovery of the outer wall is based on a novel minimal closure tracking algorithm. Our aortic segmentation method has been validated on over 3000 multiplanar reformatting (MPR) planes from 50 CT angiography data sets yielding a Dice Similarity Coefficient (DSC) of 90.67%. |
Year | Venue | Keywords |
|---|---|---|
2011 | Clinical Orthopaedics and Related Research | computed tomography,pattern recognition,ct scan |
DocType | Volume | Citations |
Journal | abs/1103.1 | 23 |
PageRank | References | Authors |
1.31 | 3 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jan Egger | 1 | 427 | 43.52 |
| Bernd Freisleben | 2 | 1456 | 142.68 |
| Randolph Setser | 3 | 46 | 3.37 |
| Rahul Renapuraar | 4 | 24 | 2.02 |
| Christina Biermann | 5 | 32 | 4.05 |
| Thomas O'Donnell | 6 | 37 | 3.94 |