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Reconstruction et classification des temps de relaxation multi-exponentielle en IRM

Abstract : -Extracting and interpreting multi-exponential relaxation time maps from noisy magnitude MRI images is an ill posed problem that requires solving a large scale inverse problem. A spatially regularized Maximum-Likelihood estimator accounting for the Rician distribution of the noise is introduced. To deal with the large-scale optimization problem, a Majoration-Minimization approach coupled with an adapted non-linear least squares algorithm is implemented. Also, we propose a method for the detection of fruit tissues and their T2 distributions using an unsupervised classification method.
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https://hal.archives-ouvertes.fr/hal-02317848
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Submitted on : Wednesday, October 16, 2019 - 2:00:30 PM
Last modification on : Wednesday, September 28, 2022 - 3:09:48 PM
Long-term archiving on: : Friday, January 17, 2020 - 3:23:09 PM

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  • HAL Id : hal-02317848, version 1
  • IRSTEA : PUB00063457

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Christian El Hajj, Saïd Moussaoui, Guylaine Collewet, Maja Musse. Reconstruction et classification des temps de relaxation multi-exponentielle en IRM. XXVIIème Colloque GRETSI sur le Traitement du Signal et des Images, Aug 2019, Lille, France. ⟨hal-02317848⟩

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