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3D multiscale vessel enhancement based centerline extraction of blood vessels


Extraction of blood vessel structure is important for improving planning, navigation and tracking in several interventional procedures. Centerline based registration methods have proven to be fast for clinical applications and an effective way of registering multi-modal images. Here, we present a novel blood vessel centerline extraction method in 3D. Our method consists of two parts, namely Multiscale Vessel Enhancement Filtering (MVEF) and Centerline Extraction using Vessel Direction (CEVD). Our proposed MVEF has an improved noise reduction and better Gaussian profile at the vessel cross-sections compared to conventional MVEF. The CEVD is our novel method for tracing the peaks of the Gaussian profile of the local MVEF at the vessel cross-sections. The peak of the Gaussian profile provides the center position of the blood vessels. The novelty of this method is in effectively finding only the connected centerlines of the blood vessels of interest. The proposed method was evaluated using both synthetic and medical images. On comparing with Frangi's vesselness filtering combined with thinning, our method is shown to be approximately 5 times faster. The results also show that our method is customized to detect only the desired blood vessels, thereby eliminating the detection of unwanted vessel-like structures. The centerline accuracy was evaluated by comparing with ground truth data created by finding Hough circle centers at each cross-section of the vessel structure. The modified symmetric Hausdorff distance between our result and the ground truth was approximately 1 pixel for both synthetic and medical images. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.


Academic chapter/article/Conference paper




  • Rahul Prasanna Kumar
  • Fritz Albregtsen
  • Martin Reimers
  • Thomas Langø
  • Bjørn Edwin
  • Ole Jakob Elle


  • Oslo University Hospital
  • University of Oslo
  • SINTEF Digital / Health Research




SPIE - The International Society for Optics and Photonics


SPIE Medical Imaging 2013: Image Processing





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