Single-view 2D/3D registation for x-ray guided bronchoscopy

  • Authors:

  • Di Xu;Sheng Xu;Daniel A. Herzka;Rex C. Yung;Martin Bergthold;Luis F. Gutierrez;Elliot R. McVeigh

  • Affiliations:

  • Department of Biomedical Engineering, Johns Hopkins University;Department of Image Guided Technology, Philips Research North America;Department of Biomedical Engineering, Johns Hopkins University;Pulmonary Oncology, Johns Hopkins Medical Institutions;Department of Digital Imaging, Philips Research Europe, Germany;Image Guided Interventions, Philips Healthcare;Department of Biomedical Engineering, Johns Hopkins University

  • Venue:
  • ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
  • Year:
  • 2010

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Abstract

X-ray guided bronchoscopy is commonly used for targeting peripheral lesions in the lungs which cannot be visualized directly by the bronchoscope. The airways and lesions are normally not visible in X-ray images, and as a result, trans bronchial biopsy of peripheral lesions is often carried out blindly, lowering the diagnostic yield of bronchoscopy. In response to this problem, we propose to superimpose the lesions and airways segmented from preoperative 3D CT images onto 2D fluoroscopic images. A feature-based 2D/3D registration method is used for image fusion between the two datasets. The algorithm extracts features of the bony structures from both CT and X-ray images to compute the registration. Phantom and clinical studies were carried out to validate the algorithm's performance, showing an accuracy of 3.48±1.38mm. The convergence range and speed of the algorithm were also evaluated to investigate the feasibility of using the algorithm clinically. The results are presented.