SIMULTANEOUS SEGMENTATION AND GRADING OF STRUCTURES FOR STATE DETERMINATION

摘要

Applicants have discovered an innovative approach to robustly and accurately detect Alzheimer's disease (AD) and prodromal forms of AD based on the distinction of specific atrophic patterns of anatomical structures such as hippocampus (HC) and entorhinal cortex (EC) in regions of interest of an image. The discovery allows to efficiently determine a pathological status and grading of pixels of interest when compared (weighed) to images from a reference library having pre-defined states. The discovery simultaneously performs segmentation and grading of structures to efficiently capture the anatomical alterations caused by AD. Based on a nonlocal patch-based framework, the grading measure estimates the similarity of the patch surrounding the voxel under study with all the patches present in different training populations.