Enabling the autofocus approach for parameter optimization in planar measurement geometry clinical optoacoustic...

Area of Science:

• Medical Imaging
• Biomedical Engineering
• Optoacoustic Imaging

Background:

• Optoacoustic (photoacoustic) tomography requires accurate tissue and detector parameters for image reconstruction.
• Conventional autofocus (AF) algorithms are computationally intensive, limiting their clinical use in planar geometry systems.

Purpose of the Study:

• To develop a computationally efficient autofocus algorithm for 3D optoacoustic tomography systems with planar geometry.
• To reduce the dimensionality of parameter estimation for faster image reconstruction.

Main Methods:

• Developed a fast autofocus (FAF) algorithm leveraging planar geometry symmetries and a virtual source concept.
• Reduced the dimensionality of the parameter estimation problem for computational simplification.

Main Results:

• The FAF algorithm achieved accurate speed of sound estimates in approximately 5 seconds.
• Validated performance using both simulated and experimental data from a near-clinical imaging system.

Conclusions:

• The FAF algorithm offers a significant computational advantage over conventional AF methods.
• FAF is expected to be crucial for the clinical adoption of 3D optoacoustic tomography with planar geometry.