Cristin-resultat-ID: 1023305
Sist endret: 31. mars 2014, 09:53
NVI-rapporteringsår: 2013
Resultat
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
2013

3D multiscale vessel enhancement based centerline extraction of blood vessels

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

Bok

SPIE Medical Imaging 2013: Image Processing
ISBN:
  • 978-08-194-9443-6

Utgiver

SPIE - The International Society for Optics and Photonics
NVI-nivå 1

Serie

Proceedings of SPIE, the International Society for Optical Engineering
ISSN 0277-786X
e-ISSN 1996-756X
NVI-nivå 1

Om resultatet

Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
Publiseringsår: 2013
Hefte: 8669
ISBN:
  • 978-08-194-9443-6

Importkilder

Isi-ID: 000322020600066

Klassifisering

Fagfelt (NPI)

Fagfelt: Elektronikk og kybernetikk
- Fagområde: Realfag og teknologi

Beskrivelse Beskrivelse

Tittel

3D multiscale vessel enhancement based centerline extraction of blood vessels

Sammendrag

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.

Bidragsytere

Rahul Prasanna Kumar

  • Tilknyttet:
    Forfatter
    ved Intervensjonssenteret ved Oslo universitetssykehus HF

Fritz Albregtsen

  • Tilknyttet:
    Forfatter
    ved Forskningsgruppen for digital signalbehandling og bildeanalyse ved Universitetet i Oslo

Martin Reimers

  • Tilknyttet:
    Forfatter
    ved Institutt for informatikk ved Universitetet i Oslo

Thomas Langø

  • Tilknyttet:
    Forfatter
    ved Helse ved SINTEF AS

Bjørn von Gohren Edwin

Bidragsyterens navn vises på dette resultatet som Bjørn Edwin
  • Tilknyttet:
    Forfatter
    ved Intervensjonssenteret ved Oslo universitetssykehus HF
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Resultatet er en del av Resultatet er en del av

SPIE Medical Imaging 2013: Image Processing.

Ourselin, Sebastien; Haynor, David. 2013, SPIE - The International Society for Optics and Photonics. UoW, UCLVitenskapelig antologi/Konferanseserie
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