Comparison of tissue parameters extracted from hyperspectral images by inverse adding-doubling and tissue indices
POSTER
Abstract
Hyperspectral imaging (HSI) is a noncontact, noninvasive method that uses UV-NIR light to capture the physiological and morphological properties of biological tissues. A promising use case of HSI is the study and diagnosis of various types of tumors by extracting tissue parameters, such as melanin and hemoglobin concentration. A well-established method for parameter extraction is the inverse adding-doubling (IAD) algorithm. Despite being faster than traditional methods like inverse Monte Carlo, it still does not allow real-time tissue parameter extraction.
This study examines various tissue indices, such as erythema and oxygenation indices, as an alternative to IAD. First, the correlation between tissue parameters extracted with IAD and tissue indices was examined on simulated skin reflectance spectra. Then, we imaged various murine tumor models and human forearms using an in-house developed HSI system covering the 400–1000 nm spectral range. Finally, IAD-extracted tissue parameters were compared to calculated tissue indices.
Preliminary results indicate a positive correlation between melanin concentration and melanin indices, as well as blood oxygenation and oxygenation indices. Tissue indices show promise for real-time tissue property extraction from hyperspectral images.
This study examines various tissue indices, such as erythema and oxygenation indices, as an alternative to IAD. First, the correlation between tissue parameters extracted with IAD and tissue indices was examined on simulated skin reflectance spectra. Then, we imaged various murine tumor models and human forearms using an in-house developed HSI system covering the 400–1000 nm spectral range. Finally, IAD-extracted tissue parameters were compared to calculated tissue indices.
Preliminary results indicate a positive correlation between melanin concentration and melanin indices, as well as blood oxygenation and oxygenation indices. Tissue indices show promise for real-time tissue property extraction from hyperspectral images.
*This work was financially supported by the state budget of the Slovenian Research Agency, research grants no. J3-3083 and no. Z1-4384, and research programs no. P3-0003, P3-0307, and P1-0389.
Presenters
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Črt Keber
- University of Ljubljana, Faculty of Mathematics and Physics
- Faculty of Mathematics and Physics, University of Ljubljana