• DocumentCode
    1817428
  • Title

    Vectorial multi-phase mouse brain tumor segmentation in T1-T2 MRI

  • Author

    Israel-Jost, V. ; Breton, E. ; Angelini, E.D. ; Choquet, Ph ; Bloch, I. ; Constantinescd, A.

  • Author_Institution
    Inst. Telecom, Telecom ParisTech, Paris, France
  • fYear
    2008
  • fDate
    14-17 May 2008
  • Firstpage
    5
  • Lastpage
    8
  • Abstract
    An automated, level-set based, segmentation framework is proposed in this work for computation of tumoral volumes on mice brain bearing gliomal tumors. Tl and T2 weighted MRI images were acquired to monitor tumor growth, at different time points. We developed an original multi-phase and multi-channel segmentation method, based on the level set framework of Chan and Vese, to facilitate the estimation of tumoral volumes. A clinical study comparing manual and segmented volumes on 18 mice demonstrate the adequacy of the multi-channel segmentation and its superiority over single-T1 channel automated segmentation in terms of measurement accuracy and correlation.
  • Keywords
    biomedical MRI; brain; image segmentation; medical image processing; tumours; T1-T2 MRI; mice brain bearing gliomal tumors; multichannel segmentation; tumor growth; vectorial multiphase segmentation; Animals; Data acquisition; Humans; Image segmentation; Level set; Magnetic resonance imaging; Mice; Neoplasms; Telecommunications; Volume measurement; MRI; Segmentation; brain tumor; level set; mice imaging; multi-channel; multi-phase;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on
  • Conference_Location
    Paris
  • Print_ISBN
    978-1-4244-2002-5
  • Electronic_ISBN
    978-1-4244-2003-2
  • Type

    conf

  • DOI
    10.1109/ISBI.2008.4540918
  • Filename
    4540918