Statistical strategy for anisotropic adventitia modelling in IVUS

Debora Gil, Aura Hernández, Oriol Rodriguez, Josepa Mauri, Petia Radeva

Research output: Contribution to journalArticleResearchpeer-review

50 Citations (Scopus)

Abstract

Vessel plaque assessment by analysis of intravascular ultrasound sequences is a useful tool for cardiac disease diagnosis and intervention. Manual detection of luminal (inner) and media-adventitia (external) vessel borders is the main activity of physicians in the process of lumen narrowing (plaque) quantification. Difficult definition of vessel border descriptors, as well as, shades, artifacts, and blurred signal response due to ultrasound physical properties trouble automated adventitia segmentation. In order to efficiently approach such a complex problem, we propose blending advanced anisotropic filtering operators and statistical classification techniques into a vessel border modelling strategy. Our systematic statistical analysis shows that the reported adventitia detection achieves an accuracy in the range of interobserver variability regardless of plaque nature, vessel geometry, and incomplete vessel borders. © 2006 IEEE.
Original languageEnglish
Article number1637534
Pages (from-to)768-778
JournalIEEE Transactions on Medical Imaging
Volume25
DOIs
Publication statusPublished - 1 Jun 2006

Keywords

  • Anisotropic processing
  • Intravascular ultrasound (IVUS)
  • Vessel border segmentation
  • Vessel structure classification

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