MATISSE: a method for improved single cell segmentation in imaging mass cytometry.

Matthijs J D BaarsNeeraj SinhaMojtaba AminiAnnelies Pieterman-BosStephanie van DamMaroussia M P GanpatMiangela M LacléBas OldenburgYvonne Vercoulen

Published in: BMC biology (2021)

MATISSE allows segmentation of densely packed cellular areas and provides a qualitative and quantitative improvement when compared to IMC-based segmentation. We expect that implementing MATISSE into tissue section analysis pipelines will yield improved cell segmentation and enable more accurate analysis of the tissue microenvironment in epithelial tissue pathologies, such as autoimmunity and cancer.

Keyphrases

single cell
deep learning
convolutional neural network
high resolution
rna seq
stem cells
papillary thyroid
high throughput
cell therapy
machine learning
squamous cell carcinoma