Affiliations: Department of Mathematics and Computer Science,
University of Missouri-St. Louis, St. Louis, MO 63121, USA. E-mail:
[email protected] | Mallinckrodt Institute of Radiology, Washington
University, St. Louis, MO 63110, USA | E-mail: [email protected] | E-mail: [email protected] | Department of Radiology, University of Iowa, Iowa
City, IA 52242, USA. E-mail: [email protected]
Abstract: Image artifacts induced by multiple metallic objects pose a
persistent problem in X-ray computed tomography (CT). Among existing CT methods
for metal artifact reduction, the wavelet-based approach we recently developed
is very promising in practice. In this paper, we report a major refinement to
our earlier work [1]. The key component of this refinement is a novel weighting
scheme for wavelet multiresolution interpolation. This weighting scheme is
designed specifically to take into account multiple metallic implants in the
field of view. In contrast to commonly used noniterative algorithms, our
algorithm identifies and corrects most seriously corrupted projection data
based on wavelet multiresolution analysis. Experimental results indicate that
the proposed algorithm significantly improves the image quality, and clearly
reveals anatomic details in the immediate vicinity of multiple metallic
implants.
