Preclassification of Broadband and Sparse Infrared Data by Multiplicative Signal Correction Approach
Abstract
:1. Introduction
2. Results
2.1. Broadband FTIR-ATR Spectra of Cartilage Samples
2.2. Preclassification Based on Broadband Spectra
2.3. Preclassification Based on Laser Wavelengths
3. Discussions
FTIR Spectra
4. Materials and Methods
4.1. Spectral Data
4.2. Annotation of Broadband Spectra for Water, Cartilage, and Low Signal Spectra
5. Theory
6. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Sample Availability
References
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Rehman, H.U.; Tafintseva, V.; Zimmermann, B.; Solheim, J.H.; Virtanen, V.; Shaikh, R.; Nippolainen, E.; Afara, I.; Saarakkala, S.; Rieppo, L.; et al. Preclassification of Broadband and Sparse Infrared Data by Multiplicative Signal Correction Approach. Molecules 2022, 27, 2298. https://doi.org/10.3390/molecules27072298
Rehman HU, Tafintseva V, Zimmermann B, Solheim JH, Virtanen V, Shaikh R, Nippolainen E, Afara I, Saarakkala S, Rieppo L, et al. Preclassification of Broadband and Sparse Infrared Data by Multiplicative Signal Correction Approach. Molecules. 2022; 27(7):2298. https://doi.org/10.3390/molecules27072298
Chicago/Turabian StyleRehman, Hafeez Ur, Valeria Tafintseva, Boris Zimmermann, Johanne Heitmann Solheim, Vesa Virtanen, Rubina Shaikh, Ervin Nippolainen, Isaac Afara, Simo Saarakkala, Lassi Rieppo, and et al. 2022. "Preclassification of Broadband and Sparse Infrared Data by Multiplicative Signal Correction Approach" Molecules 27, no. 7: 2298. https://doi.org/10.3390/molecules27072298