Optical tomography reconstruction algorithm based on the radiative transfer equation considering refractive index:...

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Computational Physics

Background:

• Optical tomography is a non-invasive imaging technique.
• Accurate reconstruction requires modeling complex optical properties like refractive index.
• Previous work established a forward model for radiative transfer equation-based optical tomography.

Purpose of the Study:

• To develop and validate an inverse model for optical tomography.
• To reconstruct images considering both uniform and gradient refractive index distributions.
• To assess the robustness and effectiveness of the reconstruction algorithm.

Main Methods:

• Utilized radiative transfer equation for optical tomography.
• Implemented adjoint difference method for uniform refractive index gradient calculation.
• Employed Lagrangian formalism for gradient refractive index gradient calculation.
• Validated the inverse model using simulated data from a human brain phantom.

Main Results:

• The forward model simulations showed good agreement with theoretical predictions.
• The inverse model successfully reconstructed images for both uniform and gradient refractive index cases.
• Reconstruction accuracy was higher for the gradient refractive index scenario.
• The developed algorithm demonstrated robustness and effectiveness.

Conclusions:

• The inverse model based on the radiative transfer equation is effective for optical tomography.
• Accounting for gradient refractive index significantly improves image reconstruction accuracy.
• The adjoint difference and Lagrangian formalism methods are suitable for gradient computation in this context.