Compressed Sensing for Biomedical Photoacoustic Imaging: A Review

Area of Science:

• Biomedical Imaging
• Optical Imaging
• Acoustic Imaging

Background:

• Photoacoustic imaging (PAI) combines optical absorption and acoustic resolution for non-invasive biomedical imaging.
• PAI detects abnormal tissues like tumors and inflammation by analyzing thermal expansion and acoustic signals.
• Current PAI systems require numerous ultrasound transducers, leading to high hardware and time costs.

Purpose of the Study:

• To introduce compressed sensing (CS) as a method to improve PAI.
• To explain how CS reconstructs high-quality images with fewer measurements.
• To discuss challenges and future directions for CS-based PAI.

Main Methods:

• Review of compressed sensing algorithms applied to PAI.
• Discussion of physical transmission model-based CS methods.
• Exploration of two-stage reconstruction and single-pixel camera-based CS methods.

Main Results:

• Compressed sensing enables PAI image reconstruction with significantly fewer measurement signals.
• CS-based PAI achieves high-quality images with reduced artifacts.
• Improved time efficiency and reduced hardware costs are key benefits of CS in PAI.

Conclusions:

• Compressed sensing is a breakthrough for photoacoustic imaging, overcoming limitations of traditional sampling.
• CS-based PAI offers a cost-effective and time-efficient solution for various biomedical applications.
• Further research into CS methods promises continued advancements in PAI technology.