Quantifying spatial relationships from whole retinal images

Microscopy advances have enabled the acquisition of large-scale biological images that capture whole tissues in situ. This in turn has fostered the study of spatial relationships between cells and various biological structures, which has proved enormously beneficial toward understanding organ and organism function. However, the unique nature of biological images and tissues precludes the application of many existing spatial mining and quantification methods necessary to make inferences about the data. Especially difficult is attempting to quantify the spatial correlation between heterogeneous structures and point objects, which often occurs in many biological tissues.