We propose a framework for the segmentation by region growing approach leveraging on feature space. It has the advantages to deal with multidimensional data and easily specify locally adaptive segmentation. It relies upon the definition of a robust neighborhood which drives the region growing. We propose two applications to illustrate this framework: a segmentation of physical parameters maps of MRI by using n-dimensional region growing and a segmentation of highly noisy image by using adaptive region growing.