A computer implemented method of generating at least one shape of a region of interest in a digital image, the method comprising: obtaining, by an image processing engine, access to a digital tissue image of a biological sample; tiling, by the image processing engine, the digital tissue image into a collection of image patches; obtaining, by the image processing engine, a plurality of features from each patch in the collection of image patches, the plurality of features defining a patch feature vector in a multidimensional feature space including the plurality of features as dimensions; determining, by the image processing engine, a user selection of a user selected subset of patches (302B, 302C) in the collection of image patches; characterized by training (509C, 509H) a one-class support vector machine (311, 313) based on the user selected subset of patches; accessing (509B, 509G) all or a predetermined number of previously selected patches (302D, 302E), and determining (509D, 509J), using the trained one-class support vector machine, a subset of the previously selected patches which are in a same class as the user selected subset of patches; training a two-class support vector machine based on the user selected subset of patches and the subset of the previously selected patches (302G, 302H); classifying, by applying the trained two-class support vector machine to patch vectors of other patches in the collection of patches, the other patches as belonging or not belonging to the same class of interest as the user selected subset of patches; and identifying one or more regions of interest based at least in part on the results of the classifying. obtaining, by an image processing engine, access to a digital tissue image of a biological sample; tiling, by the image processing engine, the digital tissue image into a collection of image patches; obtaining, by the image processing engine, a plurality of features from each patch in the collection of image patches, the plurality of features defining a patch feature vector in a multidimensional feature space including the plurality of features as dimensions; determining, by the image processing engine, a user selection of a user selected subset of patches (302B, 302C) in the collection of image patches; training (509C, 509H) a one-class support vector machine (311, 313) based on the user selected subset of patches; accessing (509B, 509G) all or a predetermined number of previously selected patches (302D, 302E), and determining (509D, 509J), using the trained one-class support vector machine, a subset of the previously selected patches which are in a same class as the user selected subset of patches; training a two-class support vector machine based on the user selected subset of patches and the subset of the previously selected patches (302G, 302H); classifying, by applying the trained two-class support vector machine to patch vectors of other patches in the collection of patches, the other patches as belonging or not belonging to the same class of interest as the user selected subset of patches; and identifying one or more regions of interest based at least in part on the results of the classifying.