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Hybrid Cone-Beam Tomographic Reconstruction: Incorporation of Prior Anatomical Models to Compensate for Missing Data

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6 Author(s)
Sadowsky, O. ; Dept. of Comput. Sci., Johns Hopkins Univ., Baltimore, MD, USA ; Junghoon Lee ; Sutter, E.G. ; Wall, S.J.
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We propose a method for improving the quality of cone-beam tomographic reconstruction done with a C-arm. C-arm scans frequently suffer from incomplete information due to image truncation, limited scan length, or other limitations. Our proposed “hybrid reconstruction” method injects information from a prior anatomical model, derived from a subject-specific computed tomography (CT) or from a statistical database (atlas), where the C-arm X-ray data is missing. This significantly reduces reconstruction artifacts with little loss of true information from the X-ray projections. The methods consist of constructing anatomical models, fast rendering of digitally reconstructed radiograph (DRR) projections of the models, rigid or deformable registration of the model and the X-ray images, and fusion of the DRR and X-ray projections, all prior to a conventional filtered back-projection algorithm. Our experiments, conducted with a mobile image intensifier C-arm, demonstrate visually and quantitatively the contribution of data fusion to image quality, which we assess through comparison to a “ground truth” CT. Importantly, we show that a significantly improved reconstruction can be obtained from a C-arm scan as short as 90° by complementing the observed projections with DRRs of two prior models, namely an atlas and a preoperative same-patient CT. The hybrid reconstruction principles are applicable to other types of C-arms as well.

Published in:

Medical Imaging, IEEE Transactions on  (Volume:30 ,  Issue: 1 )

Date of Publication:

Jan. 2011

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