1. A method comprising using at least one hardware processor for: computing a patch distinctiveness score for each of multiple patches of a medical image; computing a shape distinctiveness score for each of multiple regions of the medical image, wherein said computing of the shape distinctiveness score comprises: applying an edge detection algorithm to each of the multiple regions, to detect at least one pair of boundary edges in each of at least some of the multiple regions, for each pair of boundary edges (p, q): (a) computing a length (l pq ) of a vector ({right arrow over (pq)}) and an orientation (ψ pq ) of the vector ({right arrow over (pq)}), (b) computing a normal (θ p ) to the boundary edge (p) and a normal (θ q ) to the boundary edge (q), and (c) computing histograms for l pq , ψ pq , θ p and θ q , and computing the shape distinctiveness score for each of the at least some of the multiple regions, based on an entropy computation of the histograms; and computing a saliency map of the medical image, by combining the patch distinctiveness score and the shape distinctiveness score.