We developed a novel quantification method named shape feature using F-18 florapronol positron emission tomography–computed tomography (PET/CT) and evaluated its sensitivity and specificity for discriminating between patients with Alzheimer’s disease (AD) and patients with mild cognitive impairment or other precursors dementia (non-AD). We calculated the cerebral amyloid smoothing score (CASS) and brain atrophy index (BAI) using the surface area and volume of the region of interest in PET images. We calculated gray and white matter from trained CT data, prepared using U-net. Shape feature was calculated by multiplying CASS with BAI scores. We measured region-based standard uptake values (SUVr) and performed receiver operating characteristic (ROC) analysis to compare SUVr, shape feature, CASS, and BAI score. We investigated the relationship between shape feature and neuropsychological tests. Fifty subjects (23 with AD and 27 with non-AD) were evaluated. SUVr, shape feature, CASS, and BAI score were significantly higher in patients with AD than in those with non-AD. There was no statistically significant difference between shape feature and SUVr in ROC analysis. Shape feature correlated well with mini-mental state examination scores. Shape feature can effectively quantify beta-amyloid deposition and atrophic changes in the brain. These results suggest that shape feature is useful in the diagnosis of AD.