Embodiments access a radiological image of tissue having a tumoral volume and a peritumoral volume； define a vasculature associated with the tumoral volume； generate a Cartesian two-dimensional (2D) vessel network representation； compute a first set of localized Hough transforms based on the Cartesian 2D vessel network representation； generate a first aggregated set of peak orientations based on the first set of Hough transforms； generate a spherical 2D vessel network representation； compute a second set of localized Hough transforms based on the spherical 2D vessel network representation； generate a second aggregated set of peak orientations based on the second set of Hough transforms； generate a vascular network organization descriptor based on the aggregated peak orientations； compute a probability that the tissue is a member of a positive class based on the vascular network organization descriptor； classify the ROI based on the probability； and display the classification.
