14. A method for controlling a computer to compute a biochemical recurrence (BCR) score for a cancer patient, comprising: detecting a gland in a region of interest of a digitized histopathology section associated with the cancer patient; segmenting gland boundaries of the gland into a set of gland boundaries; calculating a directional gland tensor for the gland; constructing a localized subgraph of a gland network in the region of interest; defining pairwise spatial relationships between two or more glands in the subgraph; constructing a directional gland tensor co-occurrence matrix based, at least in part, on the pairwise spatial relationships; deriving second order statistical features from the directional gland tensor co-occurrence matrix; and controlling the computer to produce a BCR recurrence score based, at least in part, on the second order statistical features, where the BCR recurrence score predicts BCR with at least 66% accuracy.
18. The method of claim 14 , where the edges of the localized subgraph between at least one pair of glands are defined by a probabilistic decaying function, where the probabilistic decaying function minimizes the contributions of stromal regions in the region of interest by preventing edges of the subgraph from traversing heterogeneous tissues including stroma and epithelium.