• DocumentCode
    2720059
  • Title

    Automatic femur segmentation and condyle line detection in 3D MR scans for alignment of high resolution MR

  • Author

    Jolly, M.-P. ; Alvino, C. ; Odry, B. ; Deng, X. ; Zheng, J. ; Harder, M. ; Guehring, J.

  • Author_Institution
    Imaging & Visualization Dept., Siemens Corp. Res., Princeton, NJ, USA
  • fYear
    2010
  • fDate
    14-17 April 2010
  • Firstpage
    940
  • Lastpage
    943
  • Abstract
    This paper describes an automatic algorithm to extract the knee frame of reference from 3D MR isotropic scans. The method ultimately seeks to determine two lines that are tangent to the bottom of the condyles in an axial and a coronal plane. It consists of three major parts, initial detection of the knee joint using Hidden Markov Models, femur segmentation using Random Walker segmentation, and finally condyle detection. We demonstrate on 30 datasets that our algorithm is very robust and performs at the same level as a human reader.
  • Keywords
    biomedical MRI; bone; hidden Markov models; image reconstruction; image resolution; image segmentation; medical image processing; 3-D MR isotropic scan; automatic femur segmentation; condyle line detection; hidden Markov model; high resolution MR alignment; knee Scan Planning; knee joint; random walker segmentation; Coils; Hidden Markov models; High-resolution imaging; Image segmentation; Knee; Ligaments; Magnetic resonance imaging; Medical services; Planning; Visualization; Hidden Markov Models; Knee Scan Planning; Magnetic Resonance Imaging; Random Walker Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on
  • Conference_Location
    Rotterdam
  • ISSN
    1945-7928
  • Print_ISBN
    978-1-4244-4125-9
  • Electronic_ISBN
    1945-7928
  • Type

    conf

  • DOI
    10.1109/ISBI.2010.5490142
  • Filename
    5490142