Gaussian Mixture for Peak Identification in Non-Negative Least Squares Fitting of the IVIM Signal

The analysis of the Intravoxel Incoherent Motion (IVIM) signal can be performed with the Non-Negative Least Squares (NNLS) method. It allows detecting an indeterminate number of peaks associated with the multiple exponentials that compose the IVIM signal. Thus, it becomes essential to identify and classify these peaks. We performed a new method to analyze the NNLS spectrum applying the Gaussian Mixture. We obtained pseudo-diffusion maps with better contrast to visualize gliomas. Gaussian Mixture seems to replace the traditional peak search and classification algorithms, opening up possibilities to explore the NNLS spectrum.