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Conference papers

Non-local PCA-based MRI denoising

Jose Vicente Manjon 1 Pierrick Coupé 2 Antoni Buades 3
1 ITACA
2 LaBRI - Laboratoire Bordelais de Recherche en Informatique
3 MAP5 - UMR 8145 - Mathématiques Appliquées Paris 5
Abstract : This work proposes two methods for MRI denoising that exploit both the sparseness and self-similarity properties of the image. The proposed methods are based on 1) an overcomplete non-local patch grouping PCA hard thresholding and 2) a rotationally invariant nonlocal means filter that uses the output of first filter as a guide image to filter the image.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-00961154
Contributor : Pierrick Coupé <>
Submitted on : Wednesday, March 19, 2014 - 3:18:56 PM
Last modification on : Thursday, May 6, 2021 - 10:10:02 AM

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  • HAL Id : hal-00961154, version 1

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UNIV-PARIS5 | CNRS | LABRI | UNIV-BORDEAUX | MAP5 | USPC | UNIV-PARIS | UP-SCIENCES

Citation

Jose Vicente Manjon, Pierrick Coupé, Antoni Buades. Non-local PCA-based MRI denoising. Organization for Human Brain Mapping 2014 Annual Meeting, Jun 2014, Hamburg, Germany. ⟨hal-00961154⟩

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