title: Improved automated lumen contour detection by novel multifrequency processing algorithm with current intravascular ultrasound system.
abstract: OBJECTIVE
  The aim of this study was to evaluate a new fully automated lumen border tracing system based on a novel multifrequency processing algorithm.
  
  
  BACKGROUND
  We developed the multifrequency processing method to enhance arterial lumen detection by exploiting the differential scattering characteristics of blood and arterial tissue. The implementation of the method can be integrated into current intravascular ultrasound (IVUS) hardware.
  
  
  METHODS
  This study was performed in vivo with conventional 40-MHz IVUS catheters (Atlantis SR Pro™, Boston Scientific Corp, Natick, MA) in 43 clinical patients with coronary artery disease. A total of 522 frames were randomly selected, and lumen areas were measured after automatically tracing lumen borders with the new tracing system and a commercially available tracing system (TraceAssist™) referred to as the "conventional tracing system." The data assessed by the two automated systems were compared with the results of manual tracings by experienced IVUS analysts.
  
  
  RESULTS
  New automated lumen measurements showed better agreement with manual lumen area tracings compared with those of the conventional tracing system (correlation coefficient: 0.819 vs. 0.509). When compared against manual tracings, the new algorithm also demonstrated improved systematic error (mean difference: 0.13 vs. -1.02 mm(2) ) and random variability (standard deviation of difference: 2.21 vs. 4.02 mm(2) ) compared with the conventional tracing system.
  
  
  CONCLUSIONS
  This preliminary study showed that the novel fully automated tracing system based on the multifrequency processing algorithm can provide more accurate lumen border detection than current automated tracing systems and thus, offer a more reliable quantitative evaluation of lumen geometry.
authors.affiliation: Stanford University Medical Center, Stanford, CA, USA.
authors.forename: Teruyoshi
authors.initials: T
authors.lastname: Kume
authors.forename: Byeong-Keuk
authors.initials: BK
authors.lastname: Kim
authors.forename: Katsuhisa
authors.initials: K
authors.lastname: Waseda
authors.forename: Shashidhar
authors.initials: S
authors.lastname: Sathyanarayana
authors.forename: Wenguang
authors.initials: W
authors.lastname: Li
authors.forename: Tat-Jin
authors.initials: TJ
authors.lastname: Teo
authors.forename: Paul G
authors.initials: PG
authors.lastname: Yock
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Fitzgerald
authors.forename: Yasuhiro
authors.initials: Y
authors.lastname: Honda
mesh_terms: D000465:Algorithms; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging*; D003331:Coronary Vessels / Q000000981:diagnostic imaging*; D004867:Equipment Design; D006801:Humans; D007091:Image Processing, Computer-Assisted; D015203:Reproducibility of Results; D018084:Ultrasonography, Interventional / Q000295:instrumentation*