Litcius/Paper detail

Perfusion assessment via local remote photoplethysmography (rPPG)

Benjamin Kossack, Eric L. Wisotzky, Peter Eisert, Sebastian P. Schraven, Brigitta Globke, Anna Hilsmann

20222022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)26 citationsDOIOpen Access PDF

Abstract

This paper presents an approach to assess the perfusion of visible human tissue from RGB video files. We propose metrics derived from remote photoplethysmography (rPPG) signals to detect whether a tissue is adequately supplied with blood. The perfusion analysis is done in three different scales, offering a flexible approach for different applications. We perform a plane-orthogonal-to-skin rPPG independently for locally defined regions of interest on each scale. From the extracted signals, we derive the signal-to-noise ratio, magnitude in the frequency domain, heart rate, perfusion index as well as correlation between specific rPPG signals in order to locally assess the perfusion of a specific region of human tissue. We show that locally resolved rPPG has a broad range of applications. As exemplary applications, we present results in intraoperative perfusion analysis and visualization during skin and organ transplantation as well as an application for liveliness assessment for the detection of presentation attacks to authentication systems.

Topics & Concepts

PhotoplethysmogramPerfusionComputer scienceComputer visionArtificial intelligenceVisualizationRGB color modelBiomedical engineeringNoise (video)Pattern recognition (psychology)MedicineCardiologyImage (mathematics)Filter (signal processing)Non-Invasive Vital Sign MonitoringEEG and Brain-Computer InterfacesECG Monitoring and Analysis
Perfusion assessment via local remote photoplethysmography (rPPG) | Litcius