FuseMe: Classification of sMRI images by fusion of Deep CNNs in 2D+ε projections

Abstract

The methods of Content-Based visual information indexing and retrieval penetrate into Healthcare and become popular in Computer-Aided Diagnosis. Multimedia in medical images means different imaging modalities, but also multiple views of the same physiological object, such as human brain. In this paper we propose1 a multi-projection fusion approach with CNNs for diagnostics of Alzheimer Disease. Instead of working with the whole brain volume, it fuses CNNs from each brain projection sagittal, coronal, and axial ingesting a 2D+ε limited volume we have previously proposed. Three binary classification tasks are considered separating Alzheimer Disease (AD) patients from Mild Cognitive Impairment (MCI) and Normal control Subject (NC). Two fusion methods on FC-layer and on the single-projection CNN output show better performances, up to 91% and show competitive results with the SOA using heavier algorithmic chains.