Fruit tissues classification from multi-exponential T2 maps

Abstract : Water status in vegetal cells can be studied using Mutli-exponential NMR relaxation parameters. An original method improving the estimation of the transverse relaxation times from magnitude Magnetic Resonance Images (MRI) has been recently proposed1. In this method, the extraction of the T2 and I0 maps from MRI images, acquired with a multi-spin echo sequence2, is carried out using a spatially regularized optimization algorithm accounting for the Rician noise. K-means clustering is applied to the results in order to regroup voxels with similar T2 and I0 values by classes. To study the distribution of T2 values inside each class, graphs of I0 values in function of their corresponding T2 values are plotted for each class. The main composition of the fruit can be seen, with each class representing a water compartment with different T2 and I0 distributions.
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Conference papers
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Contributor : Saïd Moussaoui <>
Submitted on : Tuesday, February 26, 2019 - 11:32:15 AM
Last modification on : Tuesday, March 26, 2019 - 9:25:22 AM

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  • HAL Id : hal-02049259, version 1

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Christian El-Hajj, Guylaine Collewet, Maja Musse, Saïd Moussaoui. Fruit tissues classification from multi-exponential T2 maps. 14th International Conference on the Applications of Magnetic Resonance in Food Science, Sep 2018, Rennes, France. ⟨hal-02049259⟩

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