Development and Applications of Portable Raman Spectroscopy Combined with Artificial Intelligence for Biomedicine

Abstract

Currently, the global spectroscopic community is investigating the suitability of vibrational spectroscopy methods for point-of-care testing, histopathology, and rapid in-vivo biomedical diagnostics. Although Raman spectroscopy has many benefits, and portable Raman spectroscopy is being used in various fields successfully, currently, it has several difficulties, particularly when it comes to complex samples with low scattering cross-sections such as biological systems. The main aim of this thesis was to design and develop a portable device using Raman spectroscopy that can be utilized in conjunction with cutting-edge Artificial Intelligence (AI) techniques to obtain and analyse research-grade Raman spectrum from biological samples, which can then be further used for a variety of non-invasive biomedical investigations. Various collection and illumination optical geometries, as well as design issues, were investigated. We proposed a unique three-dimensional image reconstruction (3D tomography) approach for Universal multiple angle Raman spectroscopic (UMARS) data. Several AI/ML approaches and their significance for Raman spectroscopy with data augmentation and database standardization strategies utilized are addressed with the basic implementation of the deep learning models. We demonstrated a novel application of AI combined Raman spectroscopy for DNA-based sub-species-level classification of pathogens. In the second application, the classification of bio-carbon samples derived from pyrolysis was performed with various production conditions using Raman spectroscopy combined with deep learning algorithms such as LeNET, ResNet, and CAE. An in-house developed portable Raman spectroscopic instrument (“RAIDER”) was used to obtain the Raman spectra from complex samples such as microorganisms. Raman spectral database of highly similar 12 types of bacteria was created, and AI techniques were used for accurate classification. The instrument collected Raman signatures from a variety of bacteria samples with high SNR and compared them to commercially available benchtop instruments. Finally, the potential of an in-house developed portable Raman spectroscopic instrument for in-vivo human skin and blood analysis was explored. Research grade Raman spectra were obtained in-vivo from human skin and blood veins using in-house developed portable instrumentation with high SNR and significantly less exposure than the maximum permissible exposure limit (MPE). Further initial attempts were made to analyse in-vivo melanin content under human skin non-invasively. Variation of the melanin content was evident by biomarkers selected using PCA analysis.