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Updated: Feb 27, 2026

Three-dimensional Optical-resolution Photoacoustic Microscopy
Published on: May 3, 2011
Toroidal sensor arrays for real-time photoacoustic imaging
Anton S Bychkov1, Elena B Cherepetskaya1, Alexander A Karabutov2
1Moscow State University, Faculty of Physics, Moscow, Leninskiye Gory, RussiabNational University of Science and Technology MISiS, Moscow, Russia.
This study investigates photoacoustic (PA) and laser ultrasonic (LU) imaging using toroidal sensor arrays. Toroidal geometry enhances diagnostic capabilities for diverse materials and biological imaging.
Area of Science:
- Optics and Acoustics
- Biomedical Imaging
- Materials Science
Background:
- Photoacoustic (PA) and laser ultrasonic (LU) imaging are advanced non-destructive testing techniques.
- Image formation in these modalities is influenced by sensor array geometry.
- Complex-shaped sensor arrays, particularly concave ones, present unique challenges and opportunities for image quality.
Purpose of the Study:
- To theoretically and numerically investigate image formation in PA and LU imaging using complex-shaped concave sensor arrays.
- To assess the spatial resolution and sensitivity regions of PA and LU imaging systems.
- To explore the impact of toroidal array geometry on imaging performance.
Main Methods:
- Utilizing sensitivity maps and spatial resolution maps in the image plane for quantitative assessment.
- Theoretical modeling of image formation processes.
- Numerical simulations to analyze the performance of different array geometries.
Main Results:
- The study quantifies the spatial resolution and sensitivity regions for PA and LU imaging systems.
- A direct relationship between the size of high-sensitivity regions and spatial resolution is identified.
- Toroidal sensor arrays demonstrate a significant improvement in imaging performance.
Conclusions:
- The use of toroidal sensor arrays substantially enhances the diagnostic capabilities of PA and LU imaging.
- This improved performance is applicable to a wide range of materials, including biological objects, rocks, and composite materials.
- The findings provide valuable insights for the design and optimization of advanced imaging systems.
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