Real-time delay-multiply-and-sum beamforming with coherence factor for in vivo clinical photoacoustic imaging of humans

Seungwan Jeon,Eun-Yeong Park,Wonseok Choi,Ravi Managuli,Ki Jong Lee,Chulhong Kim

doi:10.1016/j.pacs.2019.100136

Seungwan Jeon, Eun-Yeong Park + Show 4 more

Open Access

https://doi.org/10.1016/j.pacs.2019.100136

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Abstract

In the clinical photoacoustic (PA) imaging, ultrasound (US) array transducers are typically used to provide B-mode images in real-time. To form a B-mode image, delay-and-sum (DAS) beamforming algorithm is the most commonly used algorithm because of its ease of implementation. However, this algorithm suffers from low image resolution and low contrast drawbacks. To address this issue, delay-multiply-and-sum (DMAS) beamforming algorithm has been developed to provide enhanced image quality with higher contrast, and narrower main lobe compared but has limitations on the imaging speed for clinical applications. In this paper, we present an enhanced real-time DMAS algorithm with modified coherence factor (CF) for clinical PA imaging of humans in vivo. Our algorithm improves the lateral resolution and signal-to-noise ratio (SNR) of original DMAS beamformer by suppressing the background noise and side lobes using the coherence of received signals. We optimized the computations of the proposed DMAS with CF (DMAS-CF) to achieve real-time frame rate imaging on a graphics processing unit (GPU). To evaluate the proposed algorithm, we implemented DAS and DMAS with/without CF on a clinical US/PA imaging system and quantitatively assessed their processing speed and image quality. The processing time to reconstruct one B-mode image using DAS, DAS with CF (DAS-CF), DMAS, and DMAS-CF algorithms was 7.5, 7.6, 11.1, and 11.3 ms, respectively, all achieving the real-time imaging frame rate. In terms of the image quality, the proposed DMAS-CF algorithm improved the lateral resolution and SNR by 55.4% and 93.6 dB, respectively, compared to the DAS algorithm in the phantom imaging experiments. We believe the proposed DMAS-CF algorithm and its real-time implementation contributes significantly to the improvement of imaging quality of clinical US/PA imaging system.

Highlights

Photoacoustic imaging (PAI) is a medical imaging technique based on the photoacoustic (PA) effect that converts light energy into ultrasound (US) energy
PAI has demonstrated the potential for image-based diagnosis of various diseases such as cancer [10,11], peripheral artery disease (PAD) [12], dermatitis [13], and arthritis [14]
The geometric means of full width at half maximums (FWHMs) improvement rates were 38.7%, 36.4% and 54.5% in DAS-coherence factor (CF), DMAS, and DMAS with CF (DMAS-CF) compared to DAS, respectively

Summary

Introduction

Photoacoustic imaging (PAI) is a medical imaging technique based on the photoacoustic (PA) effect that converts light energy into ultrasound (US) energy. Compared to other medical imaging techniques, PAI has several unique advantages. It can provide strong optical absorption contrasts with high ultrasonic spatial resolution in real-time [1]. This medical imaging technique is safe for humans since it does not require contrast agents or ionizing radiation [2]. It can provide functional information (e.g., oxygen saturation) as well as morphological information by using multiple wavelengths [3,4]. PAI has demonstrated the potential for image-based diagnosis of various diseases such as cancer [10,11], peripheral artery disease (PAD) [12], dermatitis [13], and arthritis [14]

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