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Accurate Super-Resolution Reconstruction for CT and MR Images

Hakimi, Wissam El ; Wesarg, Stefan (2013)
Accurate Super-Resolution Reconstruction for CT and MR Images.
Proceedings of CBMS 2013.
doi: 10.1109/CBMS.2013.6627837
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

The resolution and accuracy of medical images play an important role for early medical diagnosis, since a wrong resolution may increase the risk of making a poor decision. In practice, magnetic resonance and computed tomography images often suffer from anisotropic resolution, so that the image quality is high only within the slices. In this paper we propose a further development of a previously presented super-resolution approach, to reconstruct isotropic high resolution images from only two orthogonal low resolution data sets. Thereby, voxel uncertainties, which arise during image acquisition and preprocessing, are considered. Furthermore, an adapted inpainting method is introduced to ensure a better initial estimation of missing data. Reconstruction quality is also improved, by combining regional and local information. Experiments on synthetic and clinical data sets reveal significant improvement of image quality and accuracy, yielding better results when compared with conventional reconstruction approaches.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2013
Autor(en): Hakimi, Wissam El ; Wesarg, Stefan
Art des Eintrags: Bibliographie
Titel: Accurate Super-Resolution Reconstruction for CT and MR Images
Sprache: Englisch
Publikationsjahr: 2013
Verlag: IEEE, Inc., New York
Veranstaltungstitel: Proceedings of CBMS 2013
DOI: 10.1109/CBMS.2013.6627837
Kurzbeschreibung (Abstract):

The resolution and accuracy of medical images play an important role for early medical diagnosis, since a wrong resolution may increase the risk of making a poor decision. In practice, magnetic resonance and computed tomography images often suffer from anisotropic resolution, so that the image quality is high only within the slices. In this paper we propose a further development of a previously presented super-resolution approach, to reconstruct isotropic high resolution images from only two orthogonal low resolution data sets. Thereby, voxel uncertainties, which arise during image acquisition and preprocessing, are considered. Furthermore, an adapted inpainting method is introduced to ensure a better initial estimation of missing data. Reconstruction quality is also improved, by combining regional and local information. Experiments on synthetic and clinical data sets reveal significant improvement of image quality and accuracy, yielding better results when compared with conventional reconstruction approaches.

Freie Schlagworte: Forschungsgruppe Medical Computing (MECO), Super resolution, Reconstruction, Anisotropy, Computed tomography (CT), Magnetic resonance imaging (MRI)
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Graphisch-Interaktive Systeme
Hinterlegungsdatum: 12 Nov 2018 11:16
Letzte Änderung: 26 Jul 2021 15:28
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