Single-projection based volumetric image reconstruction and 3D tumor localization in real time for lung cancer radiotherapy

  • Authors:

  • Ruijiang Li;Xun Jia;John H. Lewis;Xuejun Gu;Michael Folkerts;Chunhua Men;Steve B. Jiang

  • Affiliations:

  • Department of Radiation Oncology, University of California San Diego, La Jolla, CA;Department of Radiation Oncology, University of California San Diego, La Jolla, CA;Department of Radiation Oncology, University of California San Diego, La Jolla, CA;Department of Radiation Oncology, University of California San Diego, La Jolla, CA;Department of Radiation Oncology, University of California San Diego, La Jolla, CA;Department of Radiation Oncology, University of California San Diego, La Jolla, CA;Department of Radiation Oncology, University of California San Diego, La Jolla, CA

  • Venue:
  • MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III
  • Year:
  • 2010

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Abstract

We have developed an algorithm for real-time volumetric image reconstruction and 3D tumor localization based on a single x-ray projection image. We first parameterize the deformation vector fields (DVF) of lung motion by principal component analysis (PCA). Then we optimize the DVF applied to a reference image by adapting the PCA coefficients such that the simulated projection of the reconstructed image matches the measured projection. The algorithm was tested on a digital phantom as well as patient data. The average relative image reconstruction error and 3D tumor localization error for the phantom is 7.5% and 0.9mm, respectively. The tumor localization error for patient is ∼2 mm. The computation time of reconstructing one volumetric image from each projection is around 0.2 and 0.3 seconds for phantom and patient, respectively, on an NVIDIA C1060 GPU. Clinical application can potentially lead to accurate 3D tumor tracking from a single imager.