NEURAL-NETWORK-BASED CLASSIFICATION OF COGNITIVELY NORMAL, DEMENTED, ALZHEIMER-DISEASE AND VASCULAR DEMENTIA FROM SINGLE-PHOTON EMISSION WITH COMPUTED-TOMOGRAPHY IMAGE DATA FROM BRAIN

Single photon emission with computed tomography (SPECT) hexamethylphen ylethyleneamineoxime technetium-99 images were analyzed by an optimal interpolative neural network (OINN) algorithm to determine whether the network could discriminate among clinically diagnosed groups of elder ly normal, Alzheimer disease (AD), and vascular dementia (VD) subjects , After initial image preprocessing and registration, image features w ere obtained that were representative of the mean regional tissue upta ke, These features were extracted from a given image by averaging the intensities over various regions defined by suitable masks, After trai ning, the network classified independent trials of patients whose clin ical diagnoses conformed to published criteria for probable AD or prob able/possible VD, For the SPECT data used in the current tests, the OI NN agreement was 80 and 86% for probable AD and probable/possible VD, respectively, These results suggest that artificial neural network met hods offer potential in diagnoses from brain images and possibly in ot her areas of scientific research where complex patterns of data may ha ve scientifically meaningful groupings that are not easily identifiabl e by the researcher.