1. A method of classifying a test subject comprising, a. collecting imaging data for a plurality of training subjects; b. collecting imaging data for a plurality of control subjects at least some of which are known to have a condition; c. collecting imaging data for said test subject; d. selecting an intensity volume of interest (VOI) for intensity analysis and a spatial volume of interest (VOI) for spatial analysis from said imaging data for said training subjects, said control subjects and said test subject; e. calculating training intensity data for said intensity VOI for said training subjects and calculating training spatial data for said spatial VOI for said training subjects; f. creating a statistical model based on said training intensity data and said training spatial data to provide a universe of subjects defined in relation to said intensity data and said spatial data; g. calculating control intensity data for said intensity VOI for said control subjects and calculating control spatial data for said control VOI for said control subjects; h. dividing said universe into at least a first region of subjects likely having said condition and a second region of subjects likely not having said condition utilizing said statistical model, control intensity data and said control spatial data; i. calculating subject intensity data for said intensity VOI for said test subject and calculating subject spatial data for said spatial VOI for said test subject; and j. applying said subject intensity data and said subject spatial data of said test subject to said classifier to provide a determination of whether said test subject falls within said first region or said second region.