Use of fuzzy edge single-photon emission computed tomography analysis in definite Alzheimer's disease - a retrospective study

Abstract

Abstract Background Definite Alzheimer's disease (AD) requires neuropathological confirmation. Single-photon emission computed tomography (SPECT) may enhance diagnostic accuracy, but due to restricted sensitivity and specificity, the role of SPECT is largely limited with regard to this purpose. Methods We propose a new method of SPECT data analysis. The method is based on a combination of parietal lobe selection (as regions-of-interest (ROI)), 3D fuzzy edge detection, and 3D watershed transformation. We applied the algorithm to three-dimensional SPECT images of human brains and compared the number of watershed regions inside the ROI between AD patients and controls. The Student's two-sample t-test was used for testing domain number equity in both groups. Results AD patients had a significantly reduced number of watershed regions compared to controls (p Conclusions Our non-invasive, relatively low-cost, and easy method can contribute to a more precise diagnosis of AD.