Significance: Photoacoustic imaging (PAI) has been greatly developed in a broad range of diagnostic applications. The efficiency of light to sound conversion in PAI is limited by the ubiquitous noise arising from the tissue background, leading to a low signal-to-noise ratio (SNR), and thus a poor quality of images. Frame averaging has been widely used to reduce the noise; however, it compromises the temporal resolution of PAI. Aim: We propose an approach for photoacoustic (PA) signal denoising based on a combination of low-pass filtering and sparse coding (LPFSC). Approach: LPFSC method is based on the fact that PA signal can be modeled as the sum of low frequency and sparse components, which allows for the reduction of noise levels using a hybrid alternating direction method of multipliers in an optimization process. Results: LPFSC method was evaluated using in-silico and experimental phantoms. The results show a 26% improvement in the peak SNR of PA signal compared to the averaging method for in-silico data. On average, LPFSC method offers a 63% improvement in the image contrast-to-noise ratio and a 33% improvement in the structural similarity index compared to the averaging method for objects located at three different depths, ranging from 10 to 20 mm, in a porcine tissue phantom. Conclusions: The proposed method is an effective tool for PA signal denoising, whereas it ultimately improves the quality of reconstructed images, especially at higher depths, without limiting the image acquisition speed.

中文翻译：

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基于稀疏编码和滤波相结合的光声图像改进

意义：光声成像 (PAI) 在广泛的诊断应用中得到了极大的发展。PAI 中光到声音的转换效率受到来自组织背景的无处不在的噪声的限制，导致信噪比 (SNR) 低，从而导致图像质量差。帧平均已被广泛用于降低噪声；然而，它损害了 PAI 的时间分辨率。目的：我们提出了一种基于低通滤波和稀疏编码 (LPFSC) 组合的光声 (PA) 信号降噪方法。方法：LPFSC 方法基于这样一个事实，即 PA 信号可以建模为低频和稀疏分量的总和，这允许在优化过程中使用乘法器的混合交替方向方法来降低噪声水平。结果：LPFSC 方法使用计算机模拟和实验体模进行评估。结果表明，与计算机内数据的平均方法相比，PA 信号的峰值 SNR 提高了 26%。平均而言，LPFSC 方法与位于三个不同深度（范围从 10 到 20 毫米）的对象的平均方法相比，图像对比度与噪声比提高了 63%，结构相似性指数提高了 33%。猪组织幻影。结论：所提出的方法是一种有效的 PA 信号去噪工具，同时它最终提高了重建图像的质量，尤其是在更高的深度，而不限制图像采集速度。平均而言，LPFSC 方法与位于三个不同深度（范围从 10 到 20 毫米）的对象的平均方法相比，图像对比度与噪声比提高了 63%，结构相似性指数提高了 33%。猪组织幻影。结论：所提出的方法是一种有效的 PA 信号去噪工具，同时它最终提高了重建图像的质量，尤其是在更高的深度，而不限制图像采集速度。平均而言，LPFSC 方法与位于三个不同深度（范围从 10 到 20 毫米）的对象的平均方法相比，图像对比度与噪声比提高了 63%，结构相似性指数提高了 33%。猪组织幻影。结论：所提出的方法是一种有效的 PA 信号去噪工具，同时它最终提高了重建图像的质量，尤其是在更高的深度，而不限制图像采集速度。