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SNR enhancement of highly-accelerated real-time cardiac MRI acquisitions based on non-local means algorithm

Authors :
Alexandru Bogdan Cernicanu
Benoît Naegel
Maurizio Tognolini
Jean-Paul Vallée
Jean-Noël Hyacinthe
Querying Graphics through Analysis and Recognition (QGAR)
INRIA Lorraine
Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA)
Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)
Source :
Medical Image Analysis, Medical Image Analysis, Elsevier, 2009, 13 (4), pp.598-608. ⟨10.1016/j.media.2009.05.006⟩, Medical Image Analysis, 2009, 13 (4), pp.598-608. ⟨10.1016/j.media.2009.05.006⟩, Medical Image Analysis, Vol. 13, No 4 (2009) pp. 598-608
Publication Year :
2007

Abstract

International audience; Real-time cardiac MRI appears as a promising technique to evaluate the mechanical function of the heart. However, ultra-fast MRI acquisitions come with an important signal-to-noise ratio (SNR) penalty, which drastically reduces the image quality. Hence, a real-time denoising approach would be desirable for SNR amelioration. In the clinical context of cardiac dysfunction assessment, long acquisitions are required and for most patients the acquisition takes place with free breathing. Hence, it is necessary to compensate respiratory motion in real-time. In this article, a real-time and interactive method for sequential registration and denoising of real-time MR cardiac images is presented. The method has been experimented on 60 fast MRI acquisitions in five healthy volunteers and five patients. These experiments assessed the feasibility of the method in a real-time context.

Details

ISSN :
13618423 and 13618415
Volume :
13
Issue :
4
Database :
OpenAIRE
Journal :
Medical image analysis
Accession number :
edsair.doi.dedup.....5b1fc2cca67273057a6cbaba9b9d0840
Full Text :
https://doi.org/10.1016/j.media.2009.05.006⟩