Correspondence-Aware Manifold Learning for Microscopic and Spatial Omics Imaging: A Novel Data Fusion Method Bringing Mass Spectrometry Imaging to a Cellular Resolution

High-dimensional molecular measurements are transforming the field of pathology into a data-driven discipline. While hematoxylin and eosin (H&E) stainings are still the gold standard to diagnose diseases, the integration of microscopic and molecular information is becoming crucial to advance our...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Analytical chemistry (Washington) 2021-02, Vol.93 (7), p.3452-3460
Hauptverfasser:	Smets, Tina, De Keyser, Tom, Tousseyn, Thomas, Waelkens, Etienne, De Moor, Bart
Format:	Artikel
Sprache:	eng
Schlagworte:	Chemistry Data integration Heterogeneity Imaging Machine learning Manifolds (mathematics) Mass spectrometry Mass spectroscopy Scientific imaging Spatial discrimination learning Spectroscopy Tissues Trends
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!