Name
Title | ||
|---|---|---|
In vivo supervised analysis of stent reendothelialization from optical coherence tomography. |
Abstract | ||
|---|---|---|
The aim of this study is to interactively assess reendothelialization of stents at an accuracy of down to a few micrometer by analyzing endovascular optical coherence tomography (OCT) sequences. Vessel wall and stent struts are automatically detected by using morphological, gradient, and symmetry operators coupled with active contour models; alerts are issued to ask for user supervision over some extreme irregular geometries caused by thrombotic lesions or dissections. A complete distance map is then computed from sparse distances measured between wall and struts. Missing values are interpolated by thin-plate spline (TPS) functions. Accuracy and robustness are increased by taking into account the inhomogeneity of data points and integrating in the same framework orthogonalized forward selection of support points, optimal selection of regularization parameters by generalized cross-validation, and rejection of detection outliers. Validation is performed on simulated data, phantom acquisitions and 11 typical in vivo OCT sequences. The comparison against manual expert measurements demonstrates a bias of the order of OCT resolution (less than 10 microm) and a standard deviation of the order of the strut width (less than 150 microm). |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/TMI.2009.2037755 | IEEE Trans. Med. Imaging |
Keywords | Field | DocType |
blood vessels,image resolution,image sequences,medical image processing,optical tomography,phantoms,splines (mathematics),stents,OCT resolution,OCT sequences,active contour models,complete distance map,dissections,endovascular optical coherence tomography,extreme irregular geometries,gradient operators,in vivo supervised analysis,morphological operators,phantom,regularization parameters,sparse distances,spline functions,stent reendothelialization,stent struts,symmetry operators,thrombotic lesions,vessel wall,Biomedical image processing,coronary artery stenting,optical coherence tomography (OCT),reendothelialization,thin-plate spline (TPS) | Active contour model,Data point,Computer vision,Optical coherence tomography,Imaging phantom,Tomography,Coherence (physics),Distance transform,Artificial intelligence,Optical tomography,Mathematics | Journal |
Volume | Issue | ISSN |
29 | 3 | 1558-254X |
Citations | PageRank | References |
3 | 0.59 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Claude Kauffmann | 1 | 39 | 3.84 |
| Pascal Motreff | 2 | 7 | 1.87 |
| Laurent Sarry | 3 | 51 | 10.10 |