Share Email Print

Proceedings Paper

Automated stent defect detection and classification with a high numerical aperture optical system
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Stent quality control is a highly critical process. Cardiovascular stents have to be inspected 100% so as no defective stent is implanted in a human body. However, this visual control is currently performed manually and every stent could need tenths of minutes to be inspected. In this paper, a novel optical inspection system is presented. By the combination of a high numerical aperture (NA) optical system, a rotational stage and a line-scan camera, unrolled sections of the outer and inner surfaces of the stent are obtained and image-processed at high speed. Defects appearing in those surfaces and also in the edges are extremely contrasted due to the shadowing effect of the high NA illumination and acquisition approach. Therefore by means of morphological operations and a sensitivity parameter, defects are detected. Based on a trained defect library, a binary classifier sorts each kind of defect through a set of scoring vectors, providing the quality operator with all the required information to finally take a decision. We expect this new approach to make defect detection completely objective and to dramatically reduce the time and cost of stent quality control stage.

Paper Details

Date Published: 26 June 2017
PDF: 11 pages
Proc. SPIE 10334, Automated Visual Inspection and Machine Vision II, 103340C (26 June 2017);
Show Author Affiliations
Carlos Bermudez, Univ. Politècnica de Catalunya (Spain)
Sensofar-Tech, S.L. (Spain)
Ferran Laguarta, Univ. Politècnica de Catalunya (Spain)
Cristina Cadevall, Univ. Politècnica de Catalunya (Spain)
Sensofar-Tech, S.L. (Spain)
Aitor Matilla, Sensofar-Tech, S.L. (Spain)
Sergi Ibañez, Sensofar Medical, S.L. (Spain)
Roger Artigas, Univ. Politècnica de Catalunya (Spain)
Sensofar-Tech, S.L. (Spain)

Published in SPIE Proceedings Vol. 10334:
Automated Visual Inspection and Machine Vision II
Jürgen Beyerer; Fernando Puente León, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?