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.
Cite
@article{arxiv.1708.07012,
title = {Variational autoencoders for tissue heterogeneity exploration from (almost) no preprocessed mass spectrometry imaging data},
author = {Paolo Inglese and James L. Alexander and Anna Mroz and Zoltan Takats and Robert Glen},
journal= {arXiv preprint arXiv:1708.07012},
year = {2017}
}
Comments
mass spectrometry imaging, variational autoencoder, desorption electrospray ionization, desi