The assessment of in vivo18F images targeting amyloid deposition is currently carried on by visual rating with an optional quantification based on standardized uptake value ratio (SUVr) measurements. We target the difficulties of image reading and possible shortcomings of the SUVr methods by validating a new semi-quantitative approach named ELBA. ELBA involves a minimal image preprocessing and does not rely on small, specific regions of interest (ROIs). It evaluates the whole brain and delivers a geometrical/intensity score to be used for ranking and dichotomic assessment. The method was applied to adniimages 18F-florbetapir images from the ADNI database. Five expert readers provided visual assessment in blind and open sessions. The longitudinal trend and the comparison to SUVr measurements were also evaluated. ELBA performed with area under the roc curve (AUC) = 0.997 versus the visual assessment. The score was significantly correlated to the SUVr values (r = 0.86, p