Multistage adaptive noise reduction technique for optical resolution photoacoustic microscopy

Area of Science:

• Biomedical Imaging
• Optical Physics
• Image Processing

Background:

• Photoacoustic microscopy (PAM) offers high resolution and deep imaging capabilities.
• PAM images are susceptible to noise, necessitating effective filtering techniques.
• Existing methods may cause blurring or fail to address diverse noise types.

Purpose of the Study:

• To develop and validate an advanced filtering method for denoising photoacoustic microscopy images.
• To enhance the signal-to-noise ratio (SNR) and preserve image details.
• To provide a robust solution for improving image quality under low laser power conditions.

Main Methods:

• Implementation of a combined filtering approach using an adaptive median filter and a nonlocal means filter.
• Application of adaptive multistage denoising to address both impulsive and background noise.
• Evaluation of the method's performance in an in vivo study.

Main Results:

• The proposed method significantly improved the signal-to-noise ratio by 16 dB in in vivo studies.
• Image details were preserved with minimal blurring, a common issue with traditional filters.
• The technique demonstrated effectiveness in enhancing image quality under noisy conditions.

Conclusions:

• The adaptive multistage denoising technique provides a substantial improvement in photoacoustic microscopy image quality.
• This method offers a strong foundation for PAM applications, particularly when limited laser power is a constraint.
• The developed filtering strategy effectively overcomes noise challenges in photoacoustic imaging.