A noise-robust deep clustering of biomolecular ions improves interpretability of mass spectrometric images.

ABSTRACT:

Motivation

Mass Spectrometry Imaging (MSI) analyzes complex biological samples such as tissues. It simultaneously characterizes the ions present in the tissue in the form of mass spectra, and the spatial distribution of the ions across the tissue in the form of ion images. Unsupervised clustering of ion images facilitates the interpretation in the spectral domain, by identifying groups of ions with similar spatial distributions. Unfortunately, many current methods for clustering ion images ignore the spatial features of the images, and are therefore unable to learn these features for clustering purposes. Alternative methods extract spatial features using deep neural networks pre-trained on natural image tasks; however, this is often inadequate since ion images are substantially noi

SUBMITTER: Guo D 

PROVIDER: S-EPMC9942547 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature