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Adaptation Approaches in Unsupervised Learning: A Survey of the State-of-the-Art and Future Directions Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Sinogram Restoration Using Confidence Maps to Reduce Metal Artifact in Computed Tomography

Authors : Louis Frédérique, Benoit Recur, Sylvain Genot, Jean-Philippe Domenger, Pascal Desbarats

Published in: Image Analysis and Recognition

Publisher: Springer International Publishing

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Abstract

Metal artifact reduction (MAR) is a well-known problem and lots of studies have been performed during the last decades. The common standard methods for MAR consist of synthesizing missing projection data by using an interpolation or in-painting process. However, no method has been yet proposed to solve MAR problem when no sinogram is available. This paper proposes a novel MAR approach using confidence maps to restore an artifacted sinogram computed directly from the reconstructed image.

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Metadata
Title
Sinogram Restoration Using Confidence Maps to Reduce Metal Artifact in Computed Tomography
Authors
Louis Frédérique
Benoit Recur
Sylvain Genot
Jean-Philippe Domenger
Pascal Desbarats
Copyright Year
2016
Book
Image Analysis and Recognition

Print ISBN: 978-3-319-41500-0

Electronic ISBN: 978-3-319-41501-7

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-41501-7_10

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