Paper Info
Title
Can the coronary artery centerline extraction in computed tomography images be improved by use of a partial volume model?
Abstract
We propose the use of a statistical partial volume (PV) model to improve coronary artery tracking in 3D cardiac computed tomography images, combined with a modified centerline extraction algorithm. PV effect is a challenge when trying to separate arteries from blood-filled cardiac cavities, causing leakage and erroneous segmentations. We include a Markov Random Field with a modified weighting scheme. First, synthetic phantoms were used to evaluate the robustness and accuracy of PV detection, as well as to determine the best settings. Average Dice similarity index obtained for PV voxels was 86%. Then cardiac images from eight patients were used to evaluate the usefulness of PV detection to separate real arteries from cavities, compared to Fuzzy C-means classification. Our PV detection scheme reduced approximately by half the number of leakages between artery and cavity. The new version of artery centerline extraction algorithm takes advantage of the PV detection capacity to separate arteries from cavities and to retrieve lowsignal small vessels. We show some preliminary qualitative results of the complete method.
Year
DOI
Venue
2010
10.1007/978-3-642-15907-7_47
ICCVG (2)
Keywords
Field
DocType
partial volume model,artery centerline extraction algorithm,pv detection scheme,pv detection capacity,coronary artery centerline extraction,blood-filled cardiac cavity,cardiac image,cardiac computed tomography image,pv voxels,pv effect,separate artery,pv detection,computed tomography,partial volume
Voxel,Artery,Computer vision,Weighting,Pattern recognition,Computer science,Markov random field,Fuzzy logic,Robustness (computer science),Artificial intelligence,Image moment,Partial volume
Conference
Volume
ISSN
ISBN
6375
0302-9743
3-642-15906-0
Citations 
PageRank 
References 
0
0.34
7
Authors
4
Name
Order
Citations
PageRank
Maria A. Zuluaga127925.84
Edgar J. F. Delgado Leyton2201.85
Marcela Hernández Hoyos322815.91
Maciej Orkisz431524.14