The aim of this study is to automatically assess reendothelialization of stents at an accuracy of down to a few microns by analyzing endovascular optical coherence tomography (OCT) sequences. Vessel wall and struts are automatically detected and complete distance map is then computed from sparse distances measured between wall and struts by thin-plate spline (TPS) interpolation. A reendothelialization score is mapped onto the geometry of the coronary artery segment. Accuracy and robustness are increased by taking into account the inhomogeneity of datapoints and integrating in the same framework orthogonalized forward selection of support points, optimal selection of regularization parameters by generalized cross-validation (GCV) and rejection of detection outliers. The comparison against manual expert measurements for a phantom study and 12 in vivo stents demonstrates no significant discordance with variability of the order of the strut thickness. © 2009 Springer-Verlag.
CITATION STYLE
Dubuisson, F., Kauffmann, C., Motreff, P., & Sarry, L. (2009). In vivo OCT coronary imaging augmented with stent reendothelialization score. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5761 LNCS, pp. 475–482). https://doi.org/10.1007/978-3-642-04268-3_59
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