Al Jedani, Safaa, Smith, Caroline I 
ORCID: 0000-0001-6878-0697, Ingham, James ORCID: 0000-0001-8938-5581, Whitley, Conor A, Ellis, Barnaby G, Triantafyllou, Asterios, Gunning, Philip J, Gardner, Peter, Risk, Janet M ORCID: 0000-0002-8770-7783, Shaw, Richard J ORCID: 0000-0001-7027-8997 et al (show 2 more authors)
(2023)
Tissue discrimination in head and neck cancer using image fusion of IR and optical microscopy.
ANALYST, 148 (17).
pp. 4189-4194.
ISSN 0003-2654, 1364-5528
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Text
D3AN00692A.pdf - Open Access published version Download (4MB) | Preview |
Abstract
A regression-based fusion algorithm has been used to merge hyperspectral Fourier transform infrared (FTIR) data with an H&E image of oral squamous cell carcinoma metastases in cervical lymphoid nodal tissue. This provides insight into the success of the ratio of FTIR absorbances at 1252 cm<sup>-1</sup> and 1285 cm<sup>-1</sup> in discriminating between these tissue types. The success is due to absorbances at these two wavenumbers being dominated by contributions from DNA and collagen, respectively. A pixel-by-pixel fit of the fused spectra to the FTIR spectra of collagen, DNA and cytokeratin reveals the contributions of these molecules to the tissue at high spatial resolution.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Humans, Carcinoma, Squamous Cell, Mouth Neoplasms, Collagen, Microscopy, Spectroscopy, Fourier Transform Infrared, Algorithms |
| Divisions: | Faculty of Health and Life Sciences Faculty of Science and Engineering > School of Physical Sciences Faculty of Health and Life Sciences > Institute of Life Courses and Medical Sciences Faculty of Health and Life Sciences > Institute of Life Courses and Medical Sciences > School of Dentistry Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 08 Aug 2023 13:41 |
| Last Modified: | 06 Dec 2024 18:39 |
| DOI: | 10.1039/d3an00692a |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3172088 |
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