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Updated: Aug 8, 2025

Three-dimensional Optical-resolution Photoacoustic Microscopy

Three-dimensional Optical-resolution Photoacoustic Microscopy

Published on: May 3, 2011

Signal restoration algorithm for photoacoustic imaging systems.

Soheil Hakakzadeh^1,2, Mohammadreza Amjadian^1,3,4,2, Yachao Zhang³

¹Electrical Engineering Department of Sharif University of Technology, Tehran, Iran.

Biomedical Optics Express

|March 6, 2023

Summary

This summary is machine-generated.

Bandwidth-limited detectors in photoacoustic (PA) imaging create ripples, degrading image quality. A new PA signal restoration algorithm effectively removes these ripples, significantly improving axial resolution and contrast in reconstructed images.

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Area of Science:

Biomedical Imaging
Optical Physics
Signal Processing

Background:

Photoacoustic (PA) imaging systems utilize detectors with limited bandwidth.
This bandwidth limitation introduces unwanted ripples into captured PA signals.
These ripples degrade image resolution, contrast, and introduce artifacts in the axial direction.

Purpose of the Study:

To develop and validate a PA signal restoration algorithm to compensate for detector bandwidth limitations.
To improve axial resolution and contrast in PA imaging.
To reduce sidelobes and artifacts in reconstructed PA images.

Main Methods:

A novel PA signal restoration algorithm was designed using a mask to extract signals at absorber positions.
The algorithm effectively removes unwanted ripples from the PA signals.
Restored PA signals were used as input for conventional reconstruction algorithms like Delay-and-Sum (DAS) and Delay-Multiply-and-Sum (DMAS).

Main Results:

The proposed restoration algorithm improved axial resolution by 45% compared to initial PA signals.
Contrast was enhanced by 16.1 dB after signal restoration.
Background artifacts were suppressed by 80% in the reconstructed images.

Conclusions:

The developed PA signal restoration algorithm effectively compensates for detector bandwidth limitations.
Restored PA signals lead to significant improvements in image resolution, contrast, and artifact reduction.
This method enhances the diagnostic potential of PA imaging systems.