Statistical approaches to Raman imaging: principal component score mapping-Reference-Cited by-同舟云学术

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Statistical approaches to Raman imaging: principal component score mapping

Published:2024 Issue:17 Volume:16 Page:2707-2720
ISSN:1759-9660
Container-title:Analytical Methods
language:en
Short-container-title:Anal. Methods

Author:

Marin Elia¹²³⁴^ORCID,Bristol Davide Redolfi¹⁵⁶^ORCID,Rondinella Alfredo³^ORCID,Lanzutti Alex³,Riello Pietro⁶^ORCID

Affiliation:

1. Ceramic Physics Laboratory, Kyoto Institute of Technology, Sakyo-ku, Matsugasaki, 606-8585 Kyoto, Japan

2. Department of Dental Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan

3. Department Polytechnic of Engineering and Architecture, University of Udine, 33100, Udine, Italy

4. Biomedical Research Center, Kyoto Institute of Technology, Sakyo-ku, Matsugasaki, Kyoto 606-8585, Japan

5. Department of Immunology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan

6. Department of Molecular Science and Nanosystems, Ca' Foscari University of Venice, Via Torino 155, 30172 Venice, Italy

Abstract

We propose and benchmark test a universal protocol for the analysis of huge Raman imaging datasets, by applying PCA on raw, unprocessed data.

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/AY/D4AY00171K

Reference42 articles.

1. Infrared and Raman Spectroscopic Imaging

2. Linear and nonlinear Raman microspectroscopy: History, instrumentation, and applications

3. Raman effect: History of the discovery

4. Raman Imaging

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