Spatially Regularized Multi-Exponential Transverse Relaxation Times Estimation from Magnitude Magnetic Resonance Images Under Rician Noise

Christian EL HAJJ, Said MOUSSAOUI, Guylaine COLLEWET, Maja MUSSE
2019 2019 IEEE International Conference on Image Processing (ICIP)  
The extraction of multi-exponential decay parameters from multi-temporal images corrupted with Rician noise and with limited time samples proves to be a challenging problem frequently encountered in clinical and food MRI studies. This work aims at proposing a method for the estimation of multiexponential transverse relaxation times from noisy magnitude MRI images. A spatially regularized Maximum-Likelihood estimator accounting for the Rician distribution of the noise is introduced. To deal with
more » ... the large-scale optimization problem, a Majoration-Minimization approach coupled with an adapted non-linear least squares algorithm is implemented. The proposed algorithm is numerically fast, stable and leads to accurate results. Its effectiveness is illustrated by an application to a simulated phantom and to magnitude multi spin echo MRI images acquired from a tomato sample.
doi:10.1109/icip.2019.8804298 dblp:conf/icip/HajjMCM19 fatcat:4b6zqnlauzgklegff24lqe3m3u