Automated three-dimensional detection of intracoronary stent struts in optical coherence tomography images

Nico Bruining*, Kenji Sihan, Jurgen Ligthart, Sebastiaan De Winter, Evelyn Regar

*Corresponding author for this work

Research output: Chapter/Conference proceedingConference proceedingAcademicpeer-review

13 Citations (Scopus)

Abstract

Optical coherence tomography (OCT) is a new intracoronary imaging tool that has been recently introduced and has become the method of choice to investigate new treatment methods for coronary artery disease. Due to the OCT's high image resolution, hundreds of stent struts are visualized per patient and therefore a computer-assisted stent strut detection method could help to improve accuracy by reducing analysis time. An automated strut detection algorithm was developed based on an adapted K-nearest neighbor method. Validation in stent just implanted resulted in a success rate of 77%. In a stent follow-up group (n=14) 6 months after implantation with tissue growth a success rate of 50% was observed. Computer-assisted stent strut detection in OCT images is well feasible in patients directly after implantation; in case of considerable tissue growth it is more challenging.

Original languageEnglish
Title of host publicationComputing in Cardiology 2011, CinC 2011
Pages221-224
Number of pages4
Publication statusPublished - 2011
EventComputing in Cardiology 2011, CinC 2011 - Hangzhou, China
Duration: 18 Sept 201121 Sept 2011

Publication series

SeriesComputing in Cardiology
Volume38
ISSN2325-8861

Conference

ConferenceComputing in Cardiology 2011, CinC 2011
Country/TerritoryChina
CityHangzhou
Period18/09/1121/09/11

Fingerprint

Dive into the research topics of 'Automated three-dimensional detection of intracoronary stent struts in optical coherence tomography images'. Together they form a unique fingerprint.

Cite this