An image processing apparatus for selecting zones of an image through segmentation, said zones containing sets of image points, comprising - at least one processing unit configured to read at least data that encode an image, - memory means in signal communication with the processing unit, containing at least a part of the data that encode said image, - entry means in signal communication with the processing unit, configured to acquire selection information about points of the image to be selected, wherein the entry means is configured to acquire from a user the selection information specifying the characteristics that the zones of the image to be selected must have, characterized in that the processing unit is configured to perform the following steps: - a pre-segmentation step, wherein the processing unit generates a model, preferably a Gaussian mixture model, based on the selection information acquired by the entry means, and wherein the processing means selects a first set of zones of the image based on said model; - a morphological dilation step, wherein, the processing unit dilates morphologically each one of the zones contained in the set generated in the pre-segmentation phase expanding its contours for generating expanded zones; - a refining step, wherein the processing unit classifies each image points into one of three sets: • a set of uncertainty points containing those points of the image for which it is not possible to establish whether they belong to the zones to be selected, on the basis of a comparison between the points belonging to said first zones and those belonging to said expanded zones, • a set of unselected points on the basis of whether the points of the image pertain to said expanded zones, and • a set of selected points on the basis of whether the points of the image pertain to said first zones; - a graph processing step, wherein the processing unit represents said sets of uncertainty points, unselected points and selected points in form of a weighted graph, wherein each node of said weighted graph represents one of the points of the image classified into said three sets (F, U, B), each arc of said weighted graph connects one node to its neighbors, and each weight of said weighted graph represents the similarity between the two nodes connected by it, and wherein said processing unit applies a graph-cut method to move the uncertainty points from the set of uncertainty points to the set of unselected points or to the set of selected points, thereby allowing removal of the set of uncertainty points and completion of the image segmentation. - at least one processing unit configured to read at least data that encode an image, - memory means in signal communication with the processing unit, containing at least a part of the data that encode said image, - entry means in signal communication with the processing unit, configured to - a pre-segmentation step, wherein the processing unit generates a model, preferably a Gaussian mixture model, based on the selection information acquired by the entry means, and wherein the processing means selects a first set of zones of the image based on said model; - a morphological dilation step, wherein, the processing unit dilates morphologically each one of the zones contained in the set generated in the pre-segmentation phase expanding its contours for generating expanded zones; - a refining step, wherein the processing unit classifies each image points into one of three sets: • a set of uncertainty points containing those points of the image for which it is not possible to establish whether they belong to the zones to be selected, on the basis of a comparison between the points belonging to said first zones and those belonging to said expanded zones, • a set of unselected points on the basis of whether the points of the image pertain to said expanded zones, and • a set of selected points on the basis of whether the points of the image pertain to said first zones; • a set of uncertainty points containing those points of the image for which it is not possible to establish whether they belong to the zones to be selected, on the basis of a comparison between the points belonging to said first zones and those belonging to said expanded zones, • a set of unselected points on the basis of whether the points of the image pertain to said expanded zones, and • a set of selected points on the basis of whether the points of the image pertain to said first zones; - a graph processing step, wherein the processing unit represents said sets of uncertainty points, unselected points and selected points in form of a weighted graph, wherein each node of said weighted graph represents one of the points of the image classified into said three sets (F, U, B), each arc of said weighted graph connects one node to its neighbors, and each weight of said weighted graph represents the similarity between the two nodes connected by it, and wherein said processing unit applies a graph-cut method to move the uncertainty points from the set of uncertainty points to the set of unselected points or to the set of selected points, thereby allowing removal of the set of uncertainty points and completion of the image segmentation.