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Selective X-Ray reconstruction and registration for pose estimation in 6 degrees of freedom

  • B. P. Selby
  • , G. Sakas
  • , S. Walter
  • , W. D. Groch
  • , U. Stilla
  • Medcom GmbH
  • Cognitive Computing and Medical Imaging
  • University of Applied Sciences
  • Teclmische Universitaet Muenchen

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

Particle beams in radiological cancer treatment provide high accuracy in dose delivery. Thus approaches from image-guided radiotherapy (TGRT) are used to overcome accuracy limitations caused by the patient misalignment in the treatment device. By comparing stereoscopic X-ray images of the patient in treatment position to a reference Computed Tomography (CT) scan, a correction of the initial patient set-up can be computed. Automatic registration of the X-ray images with digital reconstructed radiographs (DRRs) from the CT and back-projection of the transformations gives a pose correction in 5 degrees of freedom (DOF). To obtain a 6 DOF correction, DRRs have to be generated for a large amount of hypothetical alignments to find the optimal match to the X-ray images. To accelerate this time consuming process and to reduce the disturbing influence of image contents that do not match correctly, we automatically exclude regions that may not improve the resulting pose correction from the rendering as well as from the matching process. Therefore these regions are identified in the X-ray images and transferred into the plane of the respective DRR. We then perform the radon transform for DRR generation only for a subset of possible pixel values and exclude the missing information from the registration process. As a result of this approach, the time needed for a full automatic pose correction computation in 6 DOF is decreased by means of 4 and more and additionally misregistrations caused by unsuitable image contents can be avoided.

Original languageEnglish
Pages (from-to)799-804
Number of pages6
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume37
StatePublished - 2008
Externally publishedYes
Event2008 21st ISPRS International Congress for Photogrammetry and Remote Sensing - Beijing, China
Duration: 3 Jul 200811 Jul 2008

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Accuracy
  • Detection
  • Orientation
  • Radiometry
  • Registration
  • Rendering
  • Spatial
  • X-Ray

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