• DocumentCode
    3494589
  • Title

    Robust tumour tracking from 2D imaging using a population-based statistical motion model

  • Author

    Preiswerk, Frank ; Arnold, Patrik ; Fasel, Beat ; Cattin, Philippe C.

  • Author_Institution
    Med. Image Anal. Center, Univ. of Basel, Basel, Switzerland
  • fYear
    2012
  • fDate
    9-10 Jan. 2012
  • Firstpage
    209
  • Lastpage
    214
  • Abstract
    This paper describes a method for tracking a tumour using the planar projections of fiducial markers as surrogates. The projections can originate from various sources such as a beam-eye view X-ray, a portal imager or a fluoroscope. The two-dimensional position of the fiducial markers in the planar image in conjunction with a population-based statistical motion model is used to accurately predict and track the motion of a target volume during treatment. The basic assumption is that the projected surrogate locations contain valuable information about the in-plane motion of the lesion whereas the statistical motion model helps to describe the unobserved out-of-plane motion of the target volume. We analysed the accuracy with regard to varying the camera position and uncertainty in the measurement of the surrogate positions to simulate image noise and camera registration errors. The experiments showed that the tumour motion can be robustly predicted with an accuracy of 2.6 mm over a wide range of target volumes and treatment field directions despite a measurement error of σ = 2 mm for the fiducials.
  • Keywords
    diagnostic radiography; image registration; image sensors; measurement errors; medical image processing; statistical analysis; tumours; 2D imaging; beam-eye view X-ray; camera position; camera registration errors; fiducial markers; fluoroscope; in-plane motion; measurement error; out-ofplane motion; population-based statistical motion model; portal imager; projected surrogate locations; robust tumour tracking; simulate image noise; target volume; treatment field directions; two-dimensional position; Cameras; Liver; Predictive models; Solid modeling; Three dimensional displays; Tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mathematical Methods in Biomedical Image Analysis (MMBIA), 2012 IEEE Workshop on
  • Conference_Location
    Breckenridge, CO
  • Print_ISBN
    978-1-4673-0352-1
  • Electronic_ISBN
    978-1-4673-0353-8
  • Type

    conf

  • DOI
    10.1109/MMBIA.2012.6164749
  • Filename
    6164749