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; characterized by identifying, by the image processing engine, a set of target tissue patches from the collection of image patches as a function of pixel content within the collection of image patches, wherein the identification is made as a function of the variance of the patches; assigning, by the image processing engine, each target tissue patch of the set of target tissue patches an initial class probability score indicating a probability that the target tissue patch falls within a class of interest, the initial class probability score generated by a trained classifier executed on each target tissue patch; generating, by the image processing engine, a first set of tissue region seed patches by identifying target tissue patches having initial class probability scores that satisfy a first seed region criterion, the first set of tissue region seed patches comprising a subset of the set of target tissue patches, wherein the first seed region criterion is identifying any patches with an initial probability score of 0.9 and above; generating, by the image processing engine, a second set of tissue region seed patches by identifying target tissue patches having initial class probability scores that satisfy a second seed region criterion, the second set of tissue region seed patches comprising a subset of the set of target tissue patches, wherein the second seed region criterion is identifying any patches with an initial class probability of 0.5 and above; calculating, by the image processing engine, a region of interest score for each patch in the second set of tissue region seed patches as a function of initial class probability scores of neighboring patches of the second set of tissue region seed patches and a distance to patches within the first set of tissue region seed patches, wherein the distance to patches is measured in patches or in pixels; and generating, by the image processing engine, one or more region of interest shapes by grouping neighboring patches based on their region of interest scores. 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; characterized by identifying, by the image processing engine, a set of target tissue patches from the collection of image patches as a function of pixel content within the collection of image patches, wherein the identification is made as a function of the variance of the patches; assigning, by the image processing engine, each target tissue patch of the set of target tissue patches an initial class probability score indicating a probability that the target tissue patch falls within a class of interest, the initial class probability score generated by a trained classifier executed on each target tissue patch; generating, by the image processing engine, a first set of tissue region seed patches by identifying target tissue patches having initial class probability scores that satisfy a first seed region criterion, the first set of tissue region seed patches comprising a subset of the set of target tissue patches, wherein the first seed region criterion is identifying any patches with an initial probability score of 0.9 and above; generating, by the image processing engine, a second set of tissue region seed patches by identifying target tissue patches having initial class probability scores that satisfy a second seed region criterion, the second set of tissue region seed patches comprising a subset of the set of target tissue patches, wherein the second seed region criterion is identifying any patches with an initial class probability of 0.5 and above; calculating, by the image processing engine, a region of interest score for each patch in the second set of tissue region seed patches as a function of initial class probability scores of neighboring patches of the second set of tissue region seed patches and a distance to patches within the first set of tissue region seed patches, wherein the distance to patches is measured in patches or in pixels; and generating, by the image processing engine, one or more region of interest shapes by grouping neighboring patches based on their region of interest scores.