A Multi-Spectral Image Database for In-Vivo Hand Perfusion Evaluation.

The increasing prevalence of vascular diseases encourages the development of minimally invasive approaches to assess tissue perfusion. A significant challenge facing current state-of-the-art methods is their validation against clinical data. In this study, we introduce an open-source database designed to evaluate tissue perfusion during the application of an occlusion protocol. The database comprises sequences of multi-spectral images (visible and near-infrared region) from the subjects’ predominant hand and their photoplethysmography data for validation. Our study recruited 45 healthy participants, including 21 females, with an age range between 18–24 years old (standard deviation equal to 1.73). The database was evaluated using two methods for estimating skin perfusion parameters based on multi-spectral images: a Kubelka-Munk model, and a linear regression. Meanwhile, for validation purposes, the changes in oxygenated and deoxygenated hemoglobin were evaluated by photoplethysmography data as baseline perfusion parameters. The Pearson correlation between plethysmography-based perfusion parameters and those extracted from multi-spectral images was evaluated in all cases as a validation metric. Our findings demonstrated a strong Pearson correlation ( $\rho >0.7$ ) between changes in oxygenated and deoxygenated hemoglobin and multi-spectral based perfusion parameters, suggesting that the database is useful for further research related to in-vivo perfusion assessment. The primary objective of this database is to provide open-source data from a controlled occlusion protocol to evaluate new approaches based on multi-spectral images in the visible and near-infrared regions. In addition, the validation by photoplethysmography data facilitates the development and assessment of innovative tissue perfusion estimation techniques.