at Google ScholarTitle data
Schleusener, J. ; Carrer, V. ; Patzelt, A. ; Guo, S. ; Bocklitz, Thomas ; Coderch, L. ; Lademann, J. ; Darvin, M. E.:
Confocal Raman imaging of skin sections containing hair follicles using classical least squares regression and multivariate curve resolution : alternating least squares.
In: Quantum Electronics.
Vol. 49
(2019)
Issue 1
.
- pp. 6-12.
ISSN 1468-4799
DOI: https://doi.org/10.1070/QEL16901
Abstract in another language
Confocal Raman microscopy (CRM) is applied ex vivo for imaging of the spatial distribution of different skin components in skin sections containing hair follicles. For multivariate data analysis, different methods are used in order to spectrally decompose the reference spectra of the skin components (dermis, viable epidermis, stratum corneum and hair). Classical least squares regression (CLS) and multivariate curve resolution–alternating least squares (MCR-ALS) are chosen as suitable methods. In comparison to other optical methods, the advantage of CRM is molecular specificity and dispensability of labelling dyes, which is e.g. necessary in fluorescence microscopy. Therefore, a useful future application of CRM in combination with multivariate data analysis lies in the analysis of penetration routes of topically applied substances, such as cosmetic formulations or drugs into the skin, which is particularly interesting in and around hair follicles.
Further data
| Item Type: | Article in a journal |
|---|---|
| Refereed: | Yes |
| Institutions of the University: | Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie - Univ.-Prof. Dr. Thomas Wilhelm Bocklitz |
| Result of work at the UBT: | No |
| DDC Subjects: | 500 Science > 530 Physics |
| Date Deposited: | 15 May 2023 10:38 |
| Last Modified: | 15 May 2023 10:38 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/76366 |