• DocumentCode
    2723334
  • Title

    Assessing tumour vascularity with 3D contrast-enhanced ultrasound: A new semi-automated segmentation framework

  • Author

    Gasnier, A. ; Ardon, R. ; Ciofolo-Veit, C. ; Leen, E. ; Correas, J.M.

  • Author_Institution
    Philips Med. Syst. Res. Paris, Suresnes, France
  • fYear
    2010
  • fDate
    14-17 April 2010
  • Firstpage
    300
  • Lastpage
    303
  • Abstract
    3D contrast-enhanced ultrasound (CEUS) is a powerful imaging technique for tumour vascularity assessment, which is critical for radio-frequency ablation (RFA) planning or for the assessment of response to antiangiogenic therapies. In this paper, we propose a novel semi-automated method for the quantification of tumour vascularity in 3D CEUS data. We apply a two-step framework combining an interactive segmentation of the tumour necrosis followed by an automatic detection of the vascularity based on implicit representations. Experimental results on 3D CEUS images of renal cell carcinomas (RCC) show that our method is promising in terms of speed and quality.
  • Keywords
    biomedical ultrasonics; cancer; cellular biophysics; image segmentation; medical image processing; radiation therapy; radiofrequency heating; tumours; 3D contrast-enhanced ultrasound; CEUS; antiangiogenic therapy; radio-frequency ablation; renal cell carcinomas; semiautomated segmentation; tumour vascularity; Biomedical imaging; Image quality; Image segmentation; Medical treatment; Minimally invasive surgery; Patient monitoring; Radiology; Shape measurement; Tumors; Ultrasonic imaging; 3D Contrast Enhanced Ultrasound; Tumour Vascularity 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.2010.5490351
  • Filename
    5490351