Abstract
We propose a variational approach for simultaneous reconstruction and multiclass segmentation of X-ray CT images, with limited field of view and missing data. We propose a simple energy minimisation approach, loosely based on a Bayesian rationale. The resulting non convex problem is solved by alternating reconstruction steps using an iterated relaxed proximal gradient, and a proximal approach for the segmentation. Preliminary results on synthetic data demonstrate the potential of the approach for synchrotron imaging applications.
Originalsprog | Engelsk |
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Titel | Scale Space and Variational Methods in Computer Vision : 6th International Conference, SSVM 2017, Kolding, Denmark, June 4-8, 2017, Proceedings |
Redaktører | Francois Lauze, Yiqiu Dong, Anders Bjorholm Dahl |
Antal sider | 12 |
Forlag | Springer |
Publikationsdato | jun. 2017 |
Sider | 308-319 |
ISBN (Trykt) | 978-3-319-58770-7 |
ISBN (Elektronisk) | 978-3-319-58771-4 |
DOI | |
Status | Udgivet - jun. 2017 |
Begivenhed | 6th International Conference on Scale Space and Variational Methods in Computer Vision - Kolding, Danmark Varighed: 4 jun. 2017 → 8 jun. 2017 Konferencens nummer: 6 |
Konference
Konference | 6th International Conference on Scale Space and Variational Methods in Computer Vision |
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Nummer | 6 |
Land/Område | Danmark |
By | Kolding |
Periode | 04/06/2017 → 08/06/2017 |
Navn | Lecture notes in computer science |
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Vol/bind | 10302 |
ISSN | 0302-9743 |