• DocumentCode
    156368
  • Title

    Multi-slices breast ultrasound lesion segmentation using Multi-Scale Vector Field Convolution snake

  • Author

    Ben Sassi, Olfa ; Sellami, Lamia ; Ben Slima, Mohamed ; Ben Hamida, Ahmed ; Chtourou, Khalil

  • Author_Institution
    Adv. Technol. for Med. & Signals ATMS, Nat. Sch. of Eng. of Sfax, Sfax, Tunisia
  • fYear
    2014
  • fDate
    17-19 March 2014
  • Firstpage
    188
  • Lastpage
    192
  • Abstract
    This study aims to apply a novel method called Multi-scale Vector Field Convolution Snake (MVFC) to segment breast ultrasound images using all slices presenting the lesion. The key idea is to combine the Vector Field Convolution Snake (VFC) method with a two-dimensional Gaussian filter with variable standard deviations in order to make snake models less sensitive to speckle noise and to contrast quality. Experimental results show that the form of the lesion changes from one slice to another which allows achieving greater precision in the extraction of the lesion characteristics.
  • Keywords
    Gaussian processes; biomedical ultrasonics; cancer; convolution; image segmentation; medical image processing; MVFC; breast ultrasound images; contrast quality; multiscale vector field convolution snake; multislices breast ultrasound lesion segmentation; speckle noise; two-dimensional Gaussian filter; variable standard deviation; Active contours; Breast; Convolution; Image segmentation; Lesions; Ultrasonic imaging; Vectors; Breast ultrasound lesion; Multi-scale Vector Field Convolution; Multi-slices; Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Technologies for Signal and Image Processing (ATSIP), 2014 1st International Conference on
  • Conference_Location
    Sousse
  • Type

    conf

  • DOI
    10.1109/ATSIP.2014.6834604
  • Filename
    6834604