Multi-exponential MRI T2 maps: A tool to classify and characterize fruit tissues.

The estimation of multi-exponential relaxation time T and their associated amplitudes A at the voxel level has been made possible by recent developments in the field of image processing. These data are of great interest for the characterization of biological tissues, such as fruit tissues. However, they represent a high number of information, not easily interpretable. Moreover, the non-uniformity of the MRI images, which mainly directly impacts A, could induce interpretation errors. In this paper, we propose a post-processing scheme that clusters similar voxels according to the multi-exponential relaxation parameters in order to reduce the complexity of the information while avoiding the problems associated with intensity non-uniformity. We also suggest a data representation suitable for the visualization of the multi-T distribution within each tissue. We illustrate this work with results for different fruits, demonstrating the great potential of multi-T information to shed new light on fruit characterization.