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Hennersperger, C.* ; Mateus, D. ; Baust, M.* ; Navab, N.A.*

A quadratic energy minimization framework for signal loss estimation from arbitrarily sampled ultrasound data.

Lect. Notes Comput. Sc. 8674, 373-380 (2014)
DOI
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
We present a flexible and general framework to iteratively solve quadratic energy problems on a non uniform grid, targeted at ultrasound imaging. Therefore, we model input samples as the nodes of an irregular directed graph, and define energies according to the application by setting weights to the edges. To solve the energy, we derive an effective optimization scheme, which avoids both the explicit computation of a linear system, as well as the compounding of the input data on a regular grid. The framework is validated in the context of 3D ultrasound signal loss estimation with the goal of providing an uncertainty estimate for each 3D data sample. Qualitative and quantitative results for 5 subjects and two target regions, namely US of the bone and the carotid artery, show the benefits of our approach, yielding continuous loss estimates.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Herausgeber Golland, P.* ; Hata, N.* ; Barillot, C.* ; Hornegger, J.* ; Howe, R.*
ISSN (print) / ISBN 0302-9743
e-ISSN 1611-3349
ISBN 978-3-319-10469-0
Konferenztitel Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014
Konferzenzdatum 14-18 September 2014
Konferenzort Boston, United States
Zeitschrift Lecture Notes in Computer Science
Quellenangaben Band: 8674, Heft: 2, Seiten: 373-380 Artikelnummer: , Supplement: ,
Verlag Springer
Verlagsort Berlin [u.a.]
Institut(e) Institute of Computational Biology (ICB)