Unsupervised segmentation of mass spectrometric ion images characterizes morphology of tissues.

ABSTRACT:

Motivation

Mass spectrometry imaging (MSI) characterizes the spatial distribution of ions in complex biological samples such as tissues. Since many tissues have complex morphology, treatments and conditions often affect the spatial distribution of the ions in morphology-specific ways. Evaluating the selectivity and the specificity of ion localization and regulation across morphology types is biologically important. However, MSI lacks algorithms for segmenting images at both single-ion and spatial resolution.

Results

This article contributes spatial-Dirichlet Gaussian mixture model (DGMM), an algorithm and a workflow for the analyses of MSI experiments, that detects components of single-ion images with homogeneous spatial composition. The approach extends DGMMs to account for

SUBMITTER: Guo D 

PROVIDER: S-EPMC6612871 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature