Health AI Central
Peer-Reviewed Publication
Sci Adv2026;12(33):eaec5080.August 14, 2026Journal Article

Label-free biochemical imaging and time point analysis of neural organoids via deep learning-enhanced Raman microspectroscopy.

Dimitar Georgiev1,2,3, Ruoxiao Xie2, Daniel Reumann2,3, Xiaoyu Zhao2, Álvaro Fernández-Galiana2,4, Mauricio Barahona5, Molly M Stevens2,3
1Department of Computing, and UKRI Centre for Doctoral Training in AI for Healthcare, Imperial College London, London, UK SW7 2AZ.
2Department of Materials, Department of Bioengineering, and Institute of Biomedical Engineering, Imperial College London, London, UK SW7 2AZ.
3Department of Physiology, Anatomy and Genetics, Department of Engineering Science, and Kavli Institute for Nanoscience Discovery, University of Oxford, Oxford, UK OX1 3QU.
4Department of Engineering Science, University of Oxford, Oxford, UK OX1 3PJ.
5Department of Mathematics, Imperial College London, London, UK SW7 2AZ.
PubMed DOI

Abstract

Three-dimensional (3D) organoids have emerged as powerful models for studying human development, disease, and drug response in vitro. Yet, their analysis remains constrained by standard imaging and characterization techniques, which are invasive, require exogenous labeling, and offer limited multiplexing. Here, we present a noninvasive, label-free imaging platform that integrates Raman microspectr…

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