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KISS, K. ŠINDELÁŘOVÁ, A. KRBAL, L. STEJSKAL, V. MRÁZOVÁ, K. VRÁBEL, J. KAŠKA, M. MODLITBOVÁ, P. POŘÍZKA, P. KAISER, J.
Original Title
Imaging margins of skin tumors using laser-induced breakdown spectroscopy and machine learning
Type
journal article in Web of Science
Language
English
Original Abstract
Nowadays, laser-based techniques play a significant role in medicine, mainly in the ophthalmology, dermatology, and surgical fields. So far, they have presented mostly therapeutic applications, although they have considerable potential for diagnostic approaches. In our study, we focused on the application of laser-based spectroscopy in skin cancer assessment. Recently, lengthy and demanding pathological investigation has been improved with modern techniques of machine learning and analytical chemistry where elemental analysis provides further insight into the investigated phenomenon. This article deals with the complementarity of Laser-Induced Breakdown Spectroscopy (LIBS) with standard histopathology. This includes discussion on sample preparation and feasibility to perform 3D imaging of a tumor. Typical skin tumors were selected for LIBS analysis, namely cutaneous malignant melanoma, squamous cell carcinoma and the most common skin tumor basal cell carcinoma, and a benign tumor was represented by hemangioma. The imaging of biotic elements (Mg, Ca, Na, and K) provides the elemental distribution within the tissue. The elemental images were correlated with the tumor progression and its margins, as well as with the difference between healthy and tumorous tissues and the results were compared with other studies covering this topic of interest. Finally, self-organizing maps were trained and used with a k-means algorithm to cluster various matrices within the tumorous tissue and to demonstrate the potential of machine learning for processing of LIBS data.
Keywords
Laser-Induced Breakdown Spectroscopy, human skin cancer, malignant melanomy
Authors
KISS, K.; ŠINDELÁŘOVÁ, A.; KRBAL, L.; STEJSKAL, V.; MRÁZOVÁ, K.; VRÁBEL, J.; KAŠKA, M.; MODLITBOVÁ, P.; POŘÍZKA, P.; KAISER, J.
Released
1. 5. 2021
Publisher
Royal Society of Chemistry
Location
CAMBRIDGE
ISBN
1364-5544
Periodical
Journal of Analytical Atomic Spectrometry
Year of study
36
Number
5
State
United Kingdom of Great Britain and Northern Ireland
Pages from
909
Pages to
916
Pages count
8
URL
https://pubs.rsc.org/en/content/articlelanding/2021/JA/D0JA00469C#!divAbstract
Full text in the Digital Library
http://hdl.handle.net/11012/200991
BibTex
@article{BUT171885, author="Kateřina {Kiss} and Anna {Šindelářová} and Lukáš {Krbal} and Václav {Stejskal} and Kristýna {Mrázová} and Jakub {Vrábel} and Milan {Kaška} and Pavlína {Modlitbová} and Pavel {Pořízka} and Jozef {Kaiser}", title="Imaging margins of skin tumors using laser-induced breakdown spectroscopy and machine learning", journal="Journal of Analytical Atomic Spectrometry", year="2021", volume="36", number="5", pages="909--916", doi="10.1039/d0ja00469c", issn="1364-5544", url="https://pubs.rsc.org/en/content/articlelanding/2021/JA/D0JA00469C#!divAbstract" }