Multigrid-based reconstruction algorithm for quantitative photoacoustic tomography.

Area of Science:

• Biomedical Imaging
• Computational Science
• Optical Physics

Background:

• Quantitative photoacoustic tomography (QPAT) is crucial for non-invasive imaging.
• Traditional reconstruction methods can be computationally intensive, requiring many iterations.
• Efficient and reliable algorithms are needed to advance QPAT applications.

Purpose of the Study:

• To develop a novel multigrid inversion framework for QPAT reconstruction.
• To accelerate the image reconstruction process while preserving accuracy.
• To validate the proposed method using both simulated and experimental data.

Main Methods:

• Implementing a multigrid inversion framework to solve the forward and inverse problems at multiple resolutions.
• Utilizing a fixed-point iteration scheme as a cost function at each resolution level.
• Solving the optical fluence distribution and inverse problem iteratively.

Main Results:

• The multigrid inversion framework significantly reduces the number of iterations required for QPAT reconstruction.
• Simulated and experimental results demonstrate the method's effectiveness and reliability.
• Achieved comparable or improved reconstruction quality with fewer iterations compared to conventional methods.

Conclusions:

• The proposed multigrid inversion framework offers a computationally efficient solution for QPAT.
• This method enhances the practicality of QPAT by reducing reconstruction time.
• The findings support the broader adoption of advanced computational techniques in biomedical imaging.