This study?s aim was to control the stents apposition by automatically analyzing endovascular optical coherence tomography (OCT) sequences. Lumen is detected using threshold, morphological and gradient operators to run a Dijkstra algorithm. Wrong detection tagged by the user and caused by bifurcation, struts'presence, thrombotic lesions or dissections can be corrected using a morphing algorithm. Struts are also segmented by computing symmetrical and morphological operators. Euclidian distance between detected struts and wall artery initializes a stent?s complete distance map and missing data are interpolated with thin-plate spline functions. Rejection of detected outliers, regularization of parameters by generalized cross-validation and using the one-side cyclic property of the map also optimize accuracy. Several indices computed from the map provide quantitative values of malapposition. Algorithm was run on four in-vivo OCT sequences including different incomplete stent apposition?s cases. Comparison with manual expert measurements validates the segmentation?s accuracy and shows an almost perfect concordance of automated results.
['Florian Dubuisson', 'Emilie Pery', 'Lemlih Ouchchane', 'Nicolas Combaret', 'Claude Kauffmann', 'Géraud Souteyrand', 'Pascal Motreff', 'Laurent Sarry']
Automated peroperative assessment of stents apposition from OCT pullbacks