1. A method of segmenting a starting image or sequence of tridimensional images based on voxels for obtaining a tridimensional segmentation image comprising a partition into regions of interest, said image or sequence of images comprising measurements, for each voxel and in a course of n time intervals (n≧1), of a real evolution of a signal representative of at least one variable of physical, chemical or biological type of said image or sequence, which comprises the following steps: a) modeling ( 10 ) of the signal comprising a definition of a parametric model of spatio-temporal evolution of said signal, this model comprising sets of homogeneous parameters so that said sets are respectively specific to structures corresponding to said regions of interest and that each set of parameters is independent of spatial coordinates in a corresponding structure; b) extracting ( 30 ) of samples of voxels so that said samples are respectively included in said structures, this extraction comprising: (i) calculating, for each voxel of said starting image or sequence of images or else of a zone of interest of the latter, a criterion of validity of a hypothesis according to which said model of evolution of said variable within a neighborhood of this voxel is specific to one and only one of said structures, (ii) extracting of model-voxels which are defined as realizing a local maxima of said criterion, (iii) a defining, for each model-voxel, one of said samples of voxels included in said corresponding structure, in such a way that this sample exhibits an evolution of said variable which complies with that of the model of the structure to which said model-voxel belongs, then (iv) estimating, on each sample thus defined, the parameters of said model of evolution of the structure in which said sample is included; then c) merging of said samples grouping together the samples whose evolution model is specific to the same structure, said merging following, preceding or including a classification of all the voxels of said image or sequence of images or of a zone of interest of the latter by aggregation with a group of samples, in such a manner that a maximum similarity exists between the evolution of said variable for these voxels and the evolution of said model characterizing this group of samples, said segmenting obtained by the merging step.