A measure of texture, the nuclear diffuseness, was formulated for use in biological classification, and specifically to characterize quantitatively chromatin texture. Nuclear diffuseness corresponds to the amount of local intensity variation in the digitized image of a nuclear profile. As a setting in which to test the efficacy of nuclear diffuseness as a diagnostic tool, the identification of parathyroid adenoma and carcinoma was considered. Digitized images of sections of parathyroid chief cell nuclei were obtained from 16 biopsies, and the nuclear diffuseness, as well as other morphometric descriptors, were computed. With just the average nuclear diffuseness and average nuclear profile area, jackknife (leave-one-out) classification using an artificial neural network was able to diagnose correctly and unambiguously the condition (normal, parathyroid adenoma, or parathyroid carcinoma) in 15 of 16 cases. In one case, the neural network assigned a higher weight to the correct diagnosis, but was unable to distinguish between normal and adenoma conclusively.