Registration of noisy images via maximum a-posteriori estimation

Beitrag in einer Fachzeitschrift


Details zur Publikation

Autorinnen und Autoren: Suhr S, Tenbrinck D, Burger M, Modersitzki J
Zeitschrift: Lecture Notes in Computer Science
Jahr der Veröffentlichung: 2014
Band: 8545 LNCS
Seitenbereich: 231-240
ISSN: 0302-9743
Sprache: Englisch


Abstract

Biomedical image registration faces challenging problems induced by the image acquisition process of the involved modality. A common problem is the omnipresence of noise perturbations. A low signal-to-noise ratio - like in modern dynamic imaging with short acquisition times - may lead to failure or artifacts in standard image registration techniques. A common approach to deal with noise in registration is image presmoothing, which may however result in bias or loss of information. A more reasonable alternative is to directly incorporate statistical noise models into image registration. In this work we present a general framework for registration of noise perturbed images based on maximum a-posteriori estimation. This leads to variational registration inference problems with data fidelities adapted to the noise characteristics, and yields a significant improvement in robustness under noise impact and parameter choices. Using synthetic data and a popular software phantom we compare the proposed model to conventional methods recently used in biomedical imaging and discuss its potential advantages. © 2014 Springer International Publishing.


Einrichtungen weiterer Autorinnen und Autoren

Fraunhofer-Institut für Bildgestützte Medizin (MEVIS)
L’école des INGENIEURS Scientifiques
Westfälische Wilhelms-Universität (WWU) Münster


Zitierweisen

APA:
Suhr, S., Tenbrinck, D., Burger, M., & Modersitzki, J. (2014). Registration of noisy images via maximum a-posteriori estimation. Lecture Notes in Computer Science, 8545 LNCS, 231-240. https://dx.doi.org/10.1007/978-3-319-08554-8_24

MLA:
Suhr, Sebastian, et al. "Registration of noisy images via maximum a-posteriori estimation." Lecture Notes in Computer Science 8545 LNCS (2014): 231-240.

BibTeX: 

Zuletzt aktualisiert 2018-04-12 um 09:23