Abstract : We propose an automatic method to quantitatively describe the spatial organization governing populations of biological objects, such as cells, which exist in stationary histology images. This quantification is of prime importance when striving to compare different tumoral models in order to evaluate potential therapies. We compare two animal models of colorectal cancer. Our approach is based on the topographic map to automatically extract the location of the relevant biological objects. We describe their spatial organization along a continuous range of scales using second-order statistics. Using a functional analysis of variance test, we show that there are significant differences in these statistics depending on cancer model, and on the day after tumor implant.