1. Method comprising the steps of: a. setting parameters of data collection for tissue in a region of interest in an animal or human suitable to be processed by a magnetic resonance imaging (MRI) apparatus operatively associated with a processor and memory; b. obtaining via the magnetic resonance imaging apparatus and recording in memory a dataset of N MRI images of a tissue in the region of interest of size n*n that specify x, y location pixel by pixel that evolve according to a preselected aspect of time behavior; c. converting the dataset via the processor into a 3D matrix of n*n*N where N is the number of discrete samples of a function that creates a vector for each matrix location; d. determining via the processor the similarities for the vector of each matrix location to the vectors of each one of its surrounding matrix locations according to a predefined norm; e. processing the 3D matrices by aggregating matrix locations of similar vectors according to a preselected aspect of time behavior; f. creating a new n*n*N matrix that includes the aggregated matrix locations of similar vectors; g. repeating steps d, e and f q times and stopping according to convergence criterion; h. best fitting the aggregated matrix locations according to a predetermined function using the final vectors to find the function parameters; and i. presenting the parameters visually.