Paper
13 March 2009 Fiducial localization in C-arm based cone-beam CT
Author Affiliations +
Abstract
C-arm based Cone-Beam CT (CBCT) imaging enables the in-situ acquisition of three dimensional images. In the context of image-guided interventions this technology potentially reduces the complexity of a procedure's workflow. Instead of acquiring the preoperative volumetric images in a separate location and transferring the patient to the interventional suite, both imaging and intervention are carried out in the same location. A key component in image-guided interventions is image to patient registration. The most common registration approach, in clinical use, is based on fiducial markers placed on the patient's skin which are then localized in the volumetric image and in the interventional environment. When using C-arm CBCT this registration approach is challenging as in many cases the small size of the volumetric reconstruction cannot include both the skin fiducials and the organ of interest. In this paper we show that fiducial localization outside of the reconstructed volume is possible if the projection images from which the reconstruction was obtained are available. By replacing direct fiducial localization in the volumetric images with localization in the projection images we obtain the fiducial coordinates in the volume's coordinate system even when the fiducials are outside of the reconstructed region. The approach was evaluated using two anthropomorphic phantoms. When using the projection images all fiducials were localized, including those that were outside the reconstruction volume. The method's maximal localization error as evaluated using fiducials that could be directly localized in the CBCT reconstruction was 0.67 millimeters.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ziv Yaniv "Fiducial localization in C-arm based cone-beam CT", Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 72610I (13 March 2009); https://doi.org/10.1117/12.811633
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KEYWORDS
Image registration

Calibration

3D image processing

Imaging systems

Cameras

Detection and tracking algorithms

Image segmentation

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