• DocumentCode
    2835474
  • Title

    A new shape based segmentation framework using statistical and variational methods

  • Author

    Aslan, Melih S. ; Abdelmunim, Hossam ; Farag, Aly A. ; Arnold, Ben ; Mostafa, Eslam ; Xiang, Ping

  • Author_Institution
    Comput. Vision & Image Process. Lab., Univ. of Louisville, Louisville, KY, USA
  • fYear
    2011
  • fDate
    11-14 Sept. 2011
  • Firstpage
    717
  • Lastpage
    720
  • Abstract
    In this paper, we propose a new shape based segmentation and registration of the vertebral bodies (VBs) in clinical computed tomography (CT) images. The VB and surrounding organs have very close gray level information and there are no strong edges in some CT images. To overcome these challenges, image appearance and shape information of VBs are used. There are three phases of our experiments: i) the detection of the VB region using the Matched filter, ii) initial segmentation using the graph cuts which integrates the intensity and spatial interaction models, iii) registration of the shape priors and initially segmented region to obtain the final segmentation. Preliminary results show that our proposed algorithm gives very encouraging results and can solve many segmentation and registration problems.
  • Keywords
    biological organs; computerised tomography; graph theory; image registration; image segmentation; matched filters; medical image processing; shape recognition; statistical analysis; variational techniques; CT images; clinical computed tomography images; graph cuts; gray level information; matched filter; shape based registration; shape based segmentation framework; spatial interaction models; statistical methods; variational methods; vertebral bodies; Accuracy; Bones; Computed tomography; Image segmentation; Shape; Training; Vectors; Spine Bone; Vertebral Body (VB); shape based segmentation and registration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2011 18th IEEE International Conference on
  • Conference_Location
    Brussels
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4577-1304-0
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2011.6116654
  • Filename
    6116654