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Conference Papers Year : 2022

A decomposition method for directional Total Variation with application to needle reconstruction in interventional imaging

Abstract

In interventional radiology, 3D reconstruction of devices such as needles can increase the precision of procedures. Doing so with CBCT is time-consuming and increases the X-ray dose. Needles being sparse, a compressed-sensing reconstruction approach seems viable. In this paper, we thus investigate the benefits of directional total variation as an adequate prior for anisotropic devices. We introduce a decomposition method that allows several a priori directions to be considered at once as well as excludes the anatomical background that is not sparse. The capacity of the method is illustrated in simulations of limited-angle acquisitions. It allows good reconstruction of the needles from a small angular coverage, even if it cannot recover the anatomical background.
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Dates and versions

hal-03770330 , version 1 (30-11-2022)

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Marion Savanier, Cyril Riddell, Yves Trousset, Emilie Chouzenoux, Jean-Christophe Pesquet. A decomposition method for directional Total Variation with application to needle reconstruction in interventional imaging. CT MEETING 2022 - The 7th International Meeting on Image Formation in X-Ray Computed Tomography, Jun 2022, Baltimore, United States. pp.123042W, ⟨10.1117/12.2647142⟩. ⟨hal-03770330⟩
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