Compressed sensing subtracted rotational angiography with multiple sparse penalty

Hélène Langet 1, 2, 3 C. Riddell 3 Y. Trousset 3 Arthur Tenenhaus 1 Elisabeth Lahalle 1 Gilles Fleury 1 Nikos Paragios 2, 4, 5
1 E3S - Supélec Sciences des Systèmes [Gif-sur-Yvette]
2 MAS - Mathématiques Appliquées aux Systèmes - EA 4037
3 GE Healthcare - General Electric Medical Systems [Buc]
4 GALEN - Organ Modeling through Extraction, Representation and Understanding of Medical Image Content
Inria Saclay - Ile de France, Ecole Centrale Paris
5 CVN - Centre de vision numérique
Abstract : Digital Subtraction Rotational Angiography (DSRA) is a clinical protocol that allows three-dimensional (3D) visualization of vasculature during minimally invasive procedures. C-arm systems that are used to generate 3D reconstructions in interventional radiology have limited sampling rate and thus, contrast resolution. To address this particular subsampling problem, we propose a novel iterative reconstruction algorithm based on compressed sensing. To this purpose, we exploit both spatial and temporal sparsity of DSRA. For computational efficiency, we use a proximal implementation that accommodates multiple '1-penalties. Experiments on both simulated and clinical data confirm the relevance of our strategy for reducing subsampling streak artifacts.
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Hélène Langet, C. Riddell, Y. Trousset, Arthur Tenenhaus, Elisabeth Lahalle, et al.. Compressed sensing subtracted rotational angiography with multiple sparse penalty. 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI 2012) , May 2012, Barcelone, Spain. pp.884-887, ⟨10.1109/ISBI.2012.6235690⟩. ⟨hal-00725950⟩

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