Truncated Newton's optimization scheme for absorption and fluorescence optical tomography: Part I theory and...

Area of Science:

• Biomedical optics
• Medical imaging
• Computational modeling

Background:

• Non-invasive biomedical optical imaging relies on accurate photon time-of-flight measurements and computational reconstruction of tissue properties.
• Advances in instrumental and computational tools are crucial for clinical applications of near-infrared (NIR) light propagation imaging.

Purpose of the Study:

• To develop and validate an image reconstruction algorithm for mapping tissue optical properties, specifically absorption and fluorescence lifetime.
• To utilize frequency-domain photon migration (FDPM) measurements for reconstructing interior tissue optical property maps.

Main Methods:

• Formulated image reconstruction as an optimization problem.
• Employed a truncated Newton's method with a trust region to match synthetic FDPM measurements with finite element predictions.
• Utilized modified reverse automatic differentiation to minimize computational overhead and error in gradient computation.

Main Results:

• Successfully reconstructed interior tissue optical property maps from synthetic FDPM measurements.
• Demonstrated the efficacy of the optimization-based inverse solution using a truncated Newton's method.
• Showcased the computational efficiency gains from using reverse automatic differentiation.

Conclusions:

• The developed algorithm provides a robust method for reconstructing tissue optical properties from FDPM data.
• This approach advances the computational tools necessary for non-invasive biomedical optical imaging.
• The findings contribute to the development of clinically relevant photon migration imaging techniques.