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Fully automatic online geometric calibration for non-circular cone-beam CT orbits using fiducials with unknown placement.
Ma, Yiqun Q; Reynolds, Tess; Ehtiati, Tina; Weiss, Clifford; Hong, Kelvin; Theodore, Nicholas; Gang, Grace J; Stayman, J Webster.
Affiliation
  • Ma YQ; Johns Hopkins University, Baltimore, Maryland, USA.
  • Reynolds T; Faculty of Medicine and Health, University of Sydney, Sydney, Australia.
  • Ehtiati T; Siemens Healthineers, Forchheim, Germany.
  • Weiss C; Johns Hopkins University, Baltimore, Maryland, USA.
  • Hong K; Johns Hopkins University, Baltimore, Maryland, USA.
  • Theodore N; Johns Hopkins University, Baltimore, Maryland, USA.
  • Gang GJ; University of Pennsylvania, Philadelphia, USA.
  • Stayman JW; Johns Hopkins University, Baltimore, Maryland, USA.
Med Phys ; 51(5): 3245-3264, 2024 May.
Article in En | MEDLINE | ID: mdl-38573172
ABSTRACT

BACKGROUND:

Cone-beam CT (CBCT) with non-circular scanning orbits can improve image quality for 3D intraoperative image guidance. However, geometric calibration of such scans can be challenging. Existing methods typically require a prior image, specialized phantoms, presumed repeatable orbits, or long computation time.

PURPOSE:

We propose a novel fully automatic online geometric calibration algorithm that does not require prior knowledge of fiducial configuration. The algorithm is fast, accurate, and can accommodate arbitrary scanning orbits and fiducial configurations.

METHODS:

The algorithm uses an automatic initialization process to eliminate human intervention in fiducial localization and an iterative refinement process to ensure robustness and accuracy. We provide a detailed explanation and implementation of the proposed algorithm. Physical experiments on a lab test bench and a clinical robotic C-arm scanner were conducted to evaluate spatial resolution performance and robustness under realistic constraints.

RESULTS:

Qualitative and quantitative results from the physical experiments demonstrate high accuracy, efficiency, and robustness of the proposed method. The spatial resolution performance matched that of our existing benchmark method, which used a 3D-2D registration-based geometric calibration algorithm.

CONCLUSIONS:

We have demonstrated an automatic online geometric calibration method that delivers high spatial resolution and robustness performance. This methodology enables arbitrary scan trajectories and should facilitate translation of such acquisition methods in a clinical setting.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Cone-Beam Computed Tomography Limits: Humans Language: En Journal: Med Phys Year: 2024 Document type: Article Affiliation country: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Cone-Beam Computed Tomography Limits: Humans Language: En Journal: Med Phys Year: 2024 Document type: Article Affiliation country: Estados Unidos
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