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  4. Confidence map based super-resolution reconstruction
 
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2012
Conference Paper
Title

Confidence map based super-resolution reconstruction

Abstract
Magnetic Resonance Imaging and Computed Tomography usually provide highly anisotropic image data, so that the resolution in the slice-selection direction is poorer than in the in-plane directions. An isotropic high-resolution image can be reconstructed from two orthogonal scans of the same object. While combining the different data sets, all input data are usually equally weighted, without considering the fidelity level of each input information. In this paper we introduce a novel super-resolution method, which considers the fidelity level of each input data by introducing an adaptive confidence map. Experimental results on simulated and real data sets have shown the improved accuracy of reconstructed images, whose resolution approximate the original in-plane resolution in all directions. The quality of the reconstructed high resolution image was improved for noiseless input data sets, and even in the presence of different noise types with a low peak signal to noise ratio.
Author(s)
El Hakimi, Wissam
TU Darmstadt GRIS
Wesarg, Stefan  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Mainwork
Medical imaging 2012. Image processing  
Conference
Conference "Medical Imaging" 2012  
Conference "Image Processing" 2012  
DOI
10.1117/12.911535
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • super resolution

  • image enhancement

  • Forschungsgruppe Medical Computing (MECO)

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