Discretization error analysis and adaptive meshing algorithms for fluorescence diffuse optical tomography: part II.

Area of Science:

• Biomedical optics
• Medical imaging
• Computational modeling

Background:

• Fluorescence diffuse optical tomography (FDOT) is a powerful imaging technique.
• Discretization errors can significantly impact the accuracy of FDOT reconstructions.
• Existing adaptive mesh methods may not sufficiently balance error reduction with computational cost.

Purpose of the Study:

• To analyze the impact of discretization on FDOT accuracy.
• To develop novel adaptive mesh generation algorithms for FDOT.
• To reduce reconstruction errors while managing computational complexity.

Main Methods:

• Developed two new error estimates relating reconstruction error to discretization.
• Designed two adaptive mesh generation algorithms based on these error estimates.
• Conducted three-dimensional numerical simulations for validation.

Main Results:

• The new algorithms demonstrated improved accuracy, resolution, and detectability of small heterogeneities.
• Error reduction was achieved while maintaining manageable problem sizes.
• Analytical and numerical comparisons showed advantages over conventional methods.

Conclusions:

• The proposed adaptive mesh algorithms enhance FDOT image quality.
• These algorithms offer a more accurate and efficient approach to FDOT reconstruction.
• This work contributes to advancing quantitative optical imaging in biomedical applications.