1. A method for automatic processing and evaluation of an image comprising: processing image data of a digital input image of an imaged body with an image processing tool comprising a software program which is embodied in a non-transitory computer readable storage medium and executable by computer hardware; and generating, with the image processing tool, a modified digital output image having image data outputted in a graphical and/or alphanumerical format highlighting a predetermined feature or quality of a region of the imaged body, wherein the image processing tool further comprises, an image detection module including a first image processing module based on a non expert image processing algorithm, the image detecting module outputting a modified image file, and a classification or evaluation module processing modified image data in the modified image file, the classification or evaluation module including a second image processing module that includes an image processing element comprising an expert image processing algorithm, an output of the expert image processing algorithm being a further modified image file, in which pixels or voxels are highlighted corresponding to an imaged object having the predetermined feature or quality, wherein the image detection module further comprises a subsystem for extracting dynamic features of the imaged body by measuring time dependent parameters describing a spontaneous or induced time dependent behavior of the imaged body, wherein the subsystem for extracting dynamic features measures a perfusion behavior of a contrast agent in tissues of the imaged body by using a time dependent signal intensity/time curve, wherein the detection module analyzes the input image to identify groups or clusters of pixels or voxels having similar parameters defining their appearance, and wherein the detection module further defines said groups or clusters of pixels or voxels as one or more images of one or more unitary objects in the image, thereby providing an indication of a target object in the imaged body, wherein the one or more unitary object in the one or more images determined by a segmentation processing step of the image, wherein the image detection module further provides a measurement step of numeric parameters describing one or more morphological features of the one or more unitary objects in the image, wherein the detection module performs a comparison step of the numeric parameters describing the one or more morphological features of the one or more unitary objects in the one or more images with nominal reference parameters describing morphological features of searched features or qualities of the imaged body or of searched objects in the imaged body, and a selection step determining a subset of a valid unitary object in the one more unitary objects in the one or more images based on results of the comparison step, wherein the numeric parameters of the one or more morphological features are measured and subjected to comparison with nominal values related to dimensions and proportions of the one or more unitary objects in the image, wherein the nominal values relate to a shape of the one or more unitary objects, and wherein the shape of the one or more unitary objects is parameterized by having the images of the one or more unitary objects undergo a skeletonization process.