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Superresolution in MRI and its influence in statistical analysis

Pierre Kornprobst 1 Grégoire Malandain 2 Olivier Faugeras 1 R. Peeters 3 Thierry Viéville 1 S. Mierisova 3 S. Sunaert 3 P. van Hecke 3
1 ODYSSEE - Computer and biological vision
DI-ENS - Département d'informatique de l'École normale supérieure, CRISAM - Inria Sophia Antipolis - Méditerranée , ENS Paris - École normale supérieure - Paris, Inria Paris-Rocquencourt, ENPC - École des Ponts ParisTech
2 EPIDAURE - Medical imaging and robotics
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : We consider the problem of increasing the spatial resolution of fMRI images. Main contributions are: (1) the definition of the protocol to acquire shifted images in order to be able to obtain images with increased resolution in the slice shift direction; (2) the use of discontinuity preserving regularization methods to solve the problem of superresolution; (3) an evaluation of the results based on human fMRI time series. Activated areas from low, high and superresolved images are compared. We conclude on the usefulness of using superresolution for task related activation detection.
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Submitted on : Tuesday, May 23, 2006 - 7:44:04 PM
Last modification on : Tuesday, September 22, 2020 - 3:59:33 AM
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  • HAL Id : inria-00072075, version 1



Pierre Kornprobst, Grégoire Malandain, Olivier Faugeras, R. Peeters, Thierry Viéville, et al.. Superresolution in MRI and its influence in statistical analysis. [Research Report] RR-4513, INRIA. 2002. ⟨inria-00072075⟩



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