Extended Perfusion Parameter Estimation from Hyperspectral Imaging Data for Bedside Diagnostic in Medicine.

Area of Science:

• Medical Imaging
• Biophysics
• Optical Engineering

Background:

• Hyperspectral imaging (HSI) shows promise as a non-contact medical measurement technique.
• Clinical integration requires practical and valid HSI cameras and data processing.
• Calculating physiological parameters from HSI remission spectra is complex.

Purpose of the Study:

• To present a data processing method for HSI remission spectra.
• To generate layer-specific perfusion parameters and depth profiles.
• To ensure practicability and validity for clinical integration.

Main Methods:

• Developed a five-layer model of perfused tissue.
• Applied approximations and heuristic methods for radiation transport modeling.
• Solved the inverse problem for efficient parameter determination.

Main Results:

• The parameter determination process is consistent and reproducible.
• The entire spectral information is transformed into interpretable model parameters.
• The method demonstrates flexibility for various skin and wound applications.

Conclusions:

• The presented HSI data processing method facilitates clinical integration.
• Depth-dependent perfusion parameters can be accurately extracted.
• The technique supports advanced clinical applications like flap monitoring and burn diagnosis.