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Multiplex coherent anti-Stokes Raman scattering microspectroscopy of brain tissue with higher ranking data classification for biomedical imaging

Titelangaben

Pohling, Christoph ; Bocklitz, Thomas ; Duarte, Alex S. ; Emmanuello, Cinzia ; Ishikawa, Mariana S. ; Dietzeck, Benjamin ; Buckup, Tiago ; Uckermann, Ortrud ; Schackert, Gabriele ; Kirsch, Matthias ; Schmitt, Michael ; Popp, Jürgen ; Motzkus, Marcus:
Multiplex coherent anti-Stokes Raman scattering microspectroscopy of brain tissue with higher ranking data classification for biomedical imaging.
In: Journal of Biomedical Optics. Bd. 22 (2017) Heft 6 . - 066005.
ISSN 1560-2281
DOI: https://doi.org/10.1117/1.JBO.22.6.066005

Volltext

Link zum Volltext (externe URL): Volltext

Abstract

Multiplex coherent anti-Stokes Raman scattering (MCARS) microscopy was carried out to map a solid tumor in mouse brain tissue. The border between normal and tumor tissue was visualized using support vector machines (SVM) as a higher ranking type of data classification. Training data were collected separately in both tissue types, and the image contrast is based on class affiliation of the single spectra. Color coding in the image generated by SVM is then related to pathological information instead of single spectral intensities or spectral differences within the data set. The results show good agreement with the H&E stained reference and spontaneous Raman microscopy, proving the validity of the MCARS approach in combination with SVM.

Weitere Angaben

Publikationsform: Artikel in einer Zeitschrift
Begutachteter Beitrag: Ja
Institutionen der Universität: Fakultäten > Fakultät für Mathematik, Physik und Informatik > Institut für Informatik > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie - Univ.-Prof. Dr. Thomas Wilhelm Bocklitz
Titel an der UBT entstanden: Nein
Themengebiete aus DDC: 500 Naturwissenschaften und Mathematik > 530 Physik
Eingestellt am: 15 Mai 2023 12:51
Letzte Änderung: 15 Mai 2023 12:51
URI: https://eref.uni-bayreuth.de/id/eprint/76354