• DocumentCode
    686947
  • Title

    Adaptive threshold method based on PET measured lesion-to-background ratio for the estimation of Metabolic Target Volume from 18F-FDG PET images

  • Author

    Gallivanone, F. ; Fazio, Federico ; Presotto, Luca ; Gilardi, M.C. ; Canevari, Claudia ; Castiglioni, I.

  • Author_Institution
    Inst. of Bioimaging & Mol. Physiol., Segrate, Italy
  • fYear
    2013
  • fDate
    Oct. 27 2013-Nov. 2 2013
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    Most advanced radiotherapy planning can be optimized by incorporating the metabolic image of the tumour to be irradiated (Metabolic Target Volume). MTV can be properly obtained by in vivo molecular imaging studies as the volume of metabolically active tumour component. Positron EmissionTomography (PET) can provide MTV by in vivo measuring the glucose metabolism of a tumour. Aim of this work was to develop an innovative PET image segmentation method, based on an adaptive threshold of the image signal-to-noise ratio, for the estimation of the MTV. The proposed method was tested on a set of anthropomorphic phantoms proving its feasibility, operator-independency and accuracy in a clinical setting.
  • Keywords
    biochemistry; blood; cancer; image segmentation; medical image processing; molecular biophysics; phantoms; positron emission tomography; radiation therapy; tumours; 18F-FDG PET images; PET; adaptive threshold method; anthropomorphic phantoms; glucose metabolism; image segmentation; image signal-to-noise ratio; in vivo molecular imaging; lesion-to-background ratio; metabolic image; metabolic target volume estimation; metabolically active tumour component volume; operator independency; positron emissiontomography; radiotherapy planning; tumour; Computed tomography; Image segmentation; Lesions; Phantoms; Positron emission tomography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2013 IEEE
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4799-0533-1
  • Type

    conf

  • DOI
    10.1109/NSSMIC.2013.6829383
  • Filename
    6829383