Radiotherapy & Oncology
Volume 93, Issue 3 , Pages 474-478 , December 2009

A pre-clinical assessment of an atlas-based automatic segmentation tool for the head and neck

  • Richard Sims

      Affiliations

    • University Hospital Coventry Warwickshire (UHCW) NHS Trust, Coventry, UK
    • University Hospitals Leicester NHS Trust, Leicester, UK
    • Corresponding Author InformationCorresponding author. Address: Radiotherapy Physics, Leicester Royal Infirmary, University Hospitals of Leicester, Infirmary Close, Leicester, LE1 5WW, UK.
  • ,
  • Aurelie Isambert

      Affiliations

    • Institut Gustave-Roussy (IGR), Villejuif, France
  • ,
  • Vincent Grégoire

      Affiliations

    • Saint Luc University Hospital (UCL), Brussels, Belgium
  • ,
  • François Bidault

      Affiliations

    • Institut Gustave-Roussy (IGR), Villejuif, France
  • ,
  • Lydia Fresco

      Affiliations

    • University Hospital Coventry Warwickshire (UHCW) NHS Trust, Coventry, UK
  • ,
  • John Sage

      Affiliations

    • University Hospital Coventry Warwickshire (UHCW) NHS Trust, Coventry, UK
    • University Hospitals Leicester NHS Trust, Leicester, UK
  • ,
  • John Mills

      Affiliations

    • University Hospital Coventry Warwickshire (UHCW) NHS Trust, Coventry, UK
  • ,
  • Jean Bourhis

      Affiliations

    • Institut Gustave-Roussy (IGR), Villejuif, France
  • ,
  • Dimitri Lefkopoulos

      Affiliations

    • Institut Gustave-Roussy (IGR), Villejuif, France
  • ,
  • Olivier Commowick

      Affiliations

    • DosiSoft, Cachan, France
    • Institut National de Recherche et Informatique, Sophia Antipolis, France
    • Present address: Children’s Hospital, Boston, MA, USA.
  • ,
  • Mehdi Benkebil

      Affiliations

    • DosiSoft, Cachan, France
  • ,
  • Grégoire Malandain

      Affiliations

    • Institut National de Recherche et Informatique, Sophia Antipolis, France

Received 12 January 2009 ,Accepted 13 August 2009.

References 

  1. Mackie TR, Kapatoes J, Ruchala K, et al. Image guidance for precise conformal radiotherapy. Int J Radiat Oncol Biol Phys. 2003;56:89–105
  2. Geets X, Daisne J-F, Arcangeli S, et al. Inter-observer variability in the delineation of pharyngeal-laryngeal tumour, parotid glands and cervical spinal cord: comparison between CT-scan and MRI. Radiother Oncol. 2005;77:25–31
  3. Fiorino C, Reni M, Bolognesi A, Cattaneo GM, Calandrino R. Intra- and inter-observer variability in contouring prostate and seminal vesicles: implications for conformal treatment planning. Radiother Oncol. 1998;47:285–292
  4. Haas B, Coradi T, Scholz M, et al. Automatic segmentation of thoracic and pelvic CT images for radiotherapy planning using implicitly anatomic knowledge and organ-specific segmentation strategies. Phys Med Biol. 2008;53:1751–1771
  5. Wang H, Dong L, O’Daniel J, et al. Validation of an accelerated ‘demons’ algorithm for deformable image registration in radiation therapy. Phys Med Biol. 2005;50:2887–2905
  6. Wang H, Garden AS, Zhang L, et al. Performance evaluation of automatic anatomy segmentation algorithm on repeat or four-dimensional computed tomography images using deformable image registration method. Int J Radiat Oncol Biol Phys. 2008;72:210–219
  7. Isambert A, Dhermain F, Bidault F, et al. Evaluation of an atlas-based automatic segmentation software for the delineation of brain organs at risk in a radiation therapy clinical context. Radiother Oncol. 2008;87:93–99
  8. Popple RA, Griffith HR, Sawrie SM, Fiveash JB, Brezovich IA. Implementation of talairach atlas based automated brain segmentation for radiation therapy dosimetry. Technol Cancer Res Treat. 2006;5:15–21
  9. Bondiau PY, Malandain G, Chanalet S, et al. Atlas-based automatic segmentation of MR images: validation study on the brainstem in radiotherapy context. Int J Radiat Oncol Biol Phys. 2005;61:289–298
  10. Commowick O, Grégoire V, Malandain G. Atlas-based delineation of lymph node levels in head and neck computed tomography images. Radiother Oncol. 2008;87:281–289
  11. Street E, Hadjiiski L, Sahiner B, et al. Automated volume analysis of head and neck lesions on CT scans using 3D level set segmentation. Med Phys. 2007;34:4399–4408
  12. Zhang T, Yuwei C, Meldolesi E, Yan D. Automatic delineation of on-line head-and-neck computed tomography images: toward on-line adaptive radiotherapy. Int J Radiat Oncol Biol Phys. 2007;68:522–530
  13. Grégoire V, Levendag P, Ang KK, et al. CT-based delineation of lymph node levels and related CTVs in the node-negative neck: DAHANCA, EORTC, GORTEC, NCIC, RTOG consensus guidelines. Radiother Oncol. 2003;69:227–236
  14. Grégoire V, Eisbruch A, Hamoir M, Levendag P. Proposal for the delineation of the nodal CTV in the node-positive and post-operative neck. Radiother Oncol. 2006;79:15–20
  15. Guimond A, Meunier J, Thirion JP. Average brain models: a convergence study. Comput Vis Comput Understand. 2000;77:192–210
  16. Ourselin S, Roche A, Prima S, Ayache N. Block matching: a general framework to improve robustness of rigid registration of medical images. In: Int Conf Med Image Comput Assist Interv LNCS, vol. 1935. Springer, 2000. p.557–66.
  17. Commowick O, Arsigny V, Isambert A, et al. An efficient locally affine framework for the smooth registration of anatomical structures. Med Image Anal. 2008;12:427–444
  18. Dice LR. Measures of the amount of ecologic association between species. Ecology. 1945;26:297–302
  19. Bharatha A, Hirose M, Hata N, et al. Evaluation of three-dimensional finite element-based deformable registration of pre- and intraoperative prostate imaging. Med Phys. 2001;28:2551–2560
  20. Zijdenbos AP, Dawant BM, Margolin RA, Palmer AC. Morphometric analysis of white matter lesions in MR images: method and validation. IEEE Trans Med Imaging. 1994;13:716–724

PII: S0167-8140(09)00449-6

doi: 10.1016/j.radonc.2009.08.013

Radiotherapy & Oncology
Volume 93, Issue 3 , Pages 474-478 , December 2009