Paper
9 August 2023 Identifying chromophore fingerprints of brain tumor tissue on hyperspectral imaging using principal component analysis
Ivan Ezhov, Luca Giannoni, Suprosanna Shit, Frédéric Lange, Florian Kofler, Bjoern Menze, Ilias Tachtsidis, Daniel Rueckert
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Abstract
Hyperspectral imaging (HSI) is an optical technique that processes the electromagnetic spectrum at a multitude of monochromatic, adjacent frequency bands. The wide-bandwidth spectral signature of a target object’s reflectance allows fingerprinting its physical, biochemical, and physiological properties. HSI has been applied for various applications, such as remote sensing and biological tissue analysis. Recently, HSI was also used to differentiate between healthy and pathological tissue under operative conditions in a surgery room on patients diagnosed with brain tumors. In this article, we perform a statistical analysis of the brain tumor patients’ HSI scans from the HELICoiD dataset with the aim of identifying the correlation between reflectance spectra and absorption spectra of tissue chromophores. By using the principal component analysis (PCA), we determine the most relevant spectral features for intra- and inter-tissue class differentiation. Furthermore, we demonstrate that such spectral features are correlated with the spectra of cytochrome, i.e., the chromophore highly involved in (hyper) metabolic processes. Identifying such fingerprints of chromophores in reflectance spectra is a key step for automated molecular profiling and, eventually, expert-free biomarker discovery.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ivan Ezhov, Luca Giannoni, Suprosanna Shit, Frédéric Lange, Florian Kofler, Bjoern Menze, Ilias Tachtsidis, and Daniel Rueckert "Identifying chromophore fingerprints of brain tumor tissue on hyperspectral imaging using principal component analysis", Proc. SPIE 12628, Diffuse Optical Spectroscopy and Imaging IX, 1262826 (9 August 2023); https://doi.org/10.1117/12.2670775
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KEYWORDS
Tissues

Tumors

Chromophores

Blood vessels

Absorption

Principal component analysis

Absorption spectrum

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