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
Conference or Workshop Item, Bibliographie
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.
| Item Type: | Conference or Workshop Item |
|---|---|
| Erschienen: | 2013 |
| Creators: | Hakimi, Wissam El ; Wesarg, Stefan |
| Type of entry: | Bibliographie |
| Title: | Accurate Super-Resolution Reconstruction for CT and MR Images |
| Language: | English |
| Date: | 2013 |
| Publisher: | IEEE, Inc., New York |
| Event Title: | Proceedings of CBMS 2013 |
| DOI: | 10.1109/CBMS.2013.6627837 |
| 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. |
| Uncontrolled Keywords: | Forschungsgruppe Medical Computing (MECO), Super resolution, Reconstruction, Anisotropy, Computed tomography (CT), Magnetic resonance imaging (MRI) |
| Divisions: | 20 Department of Computer Science 20 Department of Computer Science > Interactive Graphics Systems |
| Date Deposited: | 12 Nov 2018 11:16 |
| Last Modified: | 26 Jul 2021 15:28 |
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