• DocumentCode
    1456472
  • Title

    Statistical-Based Tracking Technique for Linear Structures Detection: Application to Vessel Segmentation in Medical Images

  • Author

    Adel, Mouloud ; Moussaoui, Aicha ; Rasigni, Monique ; Bourennane, Salah ; Hamami, Latifa

  • Author_Institution
    Inst. FRESNEL, Domaine Univ. de St.-Jerome, Marseille, France
  • Volume
    17
  • Issue
    6
  • fYear
    2010
  • fDate
    6/1/2010 12:00:00 AM
  • Firstpage
    555
  • Lastpage
    558
  • Abstract
    Linear structures such as blood vessels in medical images are important features for computer-aided diagnosis and follow-up of many diseases. In this letter a new tracking-based segmentation method is proposed to detect blood vessels in retinal images. Bayesian segmentation with the Maximum a posteriori (MAP) Probability criterion is used for that purpose. Tests on simulated and retinal images are presented and compared with a vessel detection technique. Our method performs better results.
  • Keywords
    blood vessels; eye; image segmentation; medical diagnostic computing; object detection; probability; tracking; Bayesian segmentation; blood vessel segmentation; computer-aided diagnosis; linear structures detection; maximum a posteriori probability criterion; medical images; retinal images; statistical-based tracking technique; Edge detection; medical images; retinal vessels; statistical segmentation;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2010.2046697
  • Filename
    5439802