Variational autoencoders for tissue heterogeneity exploration from (almost) no preprocessed mass spectrometry imaging data

Abstract

The paper presents the application of Variational Autoencoders (VAE) for data dimensionality reduction and explorative analysis of mass spectrometry imaging data (MSI). The results confirm that VAEs are capable of detecting the patterns associated with the different tissue sub-types with performance than standard approaches.