Presentation
13 March 2024 Bioimaging enhanced by 2D materials and interpretable machine learning
Author Affiliations +
Abstract
Bioimaging techniques with molecular specific information will provide important insights into diagnosis, treatment, and understanding of disease pathology. To obtain molecular information, it is important to have high multiplexity and high specificity hyperspectral imaging, together with analysis techniques to interpret spectral signatures. This talk introduces pioneering discoveries and novel approaches to achieve these goals. I will introduce a new bioimaging mechanism, Raman imaging enhanced through 2D materials, an enhancement effect of molecular Raman fingerprints on the atomically-flat 2D material surfaces. It offers a new paradigm of biochemical sensing with high specificity, high multiplexity, and low noise. The selection rule for the 2D material substrates has been revealed, which is critical for device design. Hyperspectral imaging examples for brain tissues with Alzheimer’s disease will be discussed, where interpretable machine learning was further applied for new knowledge discovery. The works presented offer important guidelines to design high-performance biosensing and imaging devices, and are significant in fundamental material science and quantum science.
Conference Presentation
© (2024) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shengxi Huang "Bioimaging enhanced by 2D materials and interpretable machine learning", Proc. SPIE PC12836, Optical Biopsy XXII: Toward Real-Time Spectroscopic Imaging and Diagnosis, PC128360G (13 March 2024); https://doi.org/10.1117/12.3007613
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KEYWORDS
2D materials

Quantum machine learning

Biosensing

Design and modelling

Hyperspectral imaging

Raman spectroscopy

Pathology

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