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Three-dimensional Optical-resolution Photoacoustic Microscopy
Published on: May 3, 2011
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Improvement of LED-based photoacoustic imaging using lag-coherence factor (LCF) beamforming
Souradip Paul1, Sufayan Mulani1, Mithun Kuniyil Ajith Singh2
1School of physics, Indian Institute of Science Education and Research, Thiruvananthapuram, Kerala, India.
Medical Physics
|October 16, 2023
Summary
LED-based photoacoustic (PA) imaging offers portability and affordability but suffers from low image quality. A new lag-coherence factor (LCF) method significantly improves signal-to-noise ratio and spatial resolution for better clinical applications.
Area of Science:
- Biomedical Imaging
- Optical Imaging
- Ultrasound Technology
Background:
- LED-based photoacoustic (PA) imaging is gaining popularity due to its portability and cost-effectiveness compared to laser-based systems.
- Current limitations include low signal-to-noise ratio (SNR) and limited imaging depth, resulting in suboptimal image quality, especially for sub-surface vascular imaging.
- The common implementation uses linear ultrasound (US) probes and LED arrays, with traditional delay-and-sum (DAS) beamforming often yielding unsatisfactory results due to artifacts.
Purpose of the Study:
- To introduce and evaluate a novel weighting-based image processing technique for LED-based PA imaging.
- To improve image quality by addressing limitations of traditional beamforming algorithms like DAS.
- To enhance the clinical applicability of LED-based PA imaging systems.
Main Methods:
- A lag-coherence factor (LCF) algorithm was developed, based on spatial auto-correlation of detected PA signals.
- The LCF method utilizes a lag-delay-multiply-and-sum (DMAS) beamformer in its numerator, preceded by spatial auto-correlation of US array signals.
- The technique was validated using both 2D tissue-mimicking phantom data and 3D human volunteer imaging data from a commercial LED-based PA system.
Main Results:
- The proposed LCF method demonstrated significant LED-based PA image quality improvement when combined with the conventional DAS beamformer.
- Both phantom and volunteer imaging confirmed that LCF reduces side-lobes and artifacts compared to DAS and coherence-factor (CF) approaches.
- Quantitative evaluation showed an average improvement of approximately 20% in SNR and 25% in spatial resolution compared to the conventional CF-based DAS algorithm.
Conclusions:
- The LCF-based algorithm outperforms conventional DAS and CF algorithms by enhancing SNR and spatial resolution.
- This novel weighting technique shows promise for improving the performance of LED-based PA imaging.
- The LCF method has the potential to accelerate the clinical translation of LED-based PA imaging technologies.
