3D motion tracking of pulmonary lesions using CT fluoroscopy images for robotically assisted lung biopsy

Sheng Xu, Gabor Fichtinger, Russell H. Taylor, Kevin Cleary

Research output: Contribution to journalConference articlepeer-review

Abstract

We are developing a prototype system for robotically assisted lung biopsy. For directing the robot in biopsy needle placement, we propose a non-invasive algorithm to track the 3D position of the target lesion using 2D CT fluoroscopy image sequences. A small region of the CT fluoroscopy image is registered to a corresponding region in a pre-operative CT volume to infer the position of the target lesion with respect to the imaging plane. The registration is implemented in a coarse to fine fashion. The local deformation between the two regions is modeled by an affine transformation. The sum-of-squared-differences (SSD) between the two regions is minimized using the Levenberg-Marquardt method. Multi-resolution and multi-start strategies are used to avoid local minima. As a result, multiple candidate transformations between the two regions are obtained, from which the true transformation is selected by similarity voting. The true transformation of each frame of the CT fluoroscopy image is then incorporated into a Kalman filter to predict the lesion's position for the next frame. Tests were completed to evaluate the performance of the algorithm using a respiratory motion simulator and a swine animal study.

Original languageEnglish (US)
Pages (from-to)394-402
Number of pages9
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5367
DOIs
StatePublished - Oct 27 2004
EventProgress in Biomedical Optics and Imaging 2004 - Medical Imaging: Visualization, Image-Guided Procedures, and Display - San Diego, CA, United States
Duration: Feb 15 2004Feb 17 2004

Keywords

  • Data association
  • Lung biopsy
  • Motion estimation
  • Real-time tracking
  • Robotics
  • Robust tracking
  • Textured regions

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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