Artificial Neural Network for Intravoxel Incoherent Motion Fitting: an Application in Glioma

We proposed an Artificial Neural Network (ANN) to fit the IVIM images and estimate diffusion, pseudo-diffusion, and perfusion fraction values. The ANN was first trained with simulated data and tested with images of 40 healthy controls and one patient with glioma. ANN provided parameter values similar to those obtained with a standard fitting method, but D* maps with less noise. The ANN fitting process was less time-consuming and was shown to be a possible tool for replacing a standard fitting algorithm.