Photoacoustic dermoscopy (PAD) has been proven to visualize the microvascular network within the dermis noninvasively, and has great application potential and advantages. In practice, some subjects are children or unwell and may have difficulty in controlling their breathing or trembling. The artifacts caused by the uncontrollable trembling will degrade the image quality, resulting in deviation of the pathophysiological features. This work introduces a subpixel and on-line motion correction method for clinical application of PAD. The high-accuracy motion correction was realized by the subpixel motion estimation, which was achieved by five-fold upsampling the cross-correlation matrix between A-lines or B-scan images. Since the motion correction algorithm only takes the acquired data as a priori, it can be processed immediately when a B-scan is input, so it can be embedded in the acquisition program, leading to the motion correction during the data acquisition. Moreover, the algorithm was verified by the experimental data of human skin. The results demonstrated that the images after sub-pixel motion correction are obviously improved visually, and the structural similarity index measurement (SSIM) and peak signal-to-noise ratio (PSNR) between adjacent B-scan images after correction are increased by 31.6% and 47.7% compared to the uncorrected images. To conclude, the proposed algorithm can make it robust in terms of accuracy and reliability and will help PAD fulfill its clinical promise.

中文翻译：

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用于光声皮肤镜检查的亚像素和在线运动校正

光声皮肤镜（PAD）已被证明可以无创地可视化真皮内的微血管网络，具有巨大的应用潜力和优势。在实践中，一些受试者是儿童或身体不适，并且可能难以控制他们的呼吸或颤抖。由无法控制的颤抖引起的伪影会降低图像质量，导致病理生理特征的偏差。这项工作介绍了一种用于 PAD 临床应用的亚像素和在线运动校正方法。高精度运动校正是通过亚像素运动估计实现的，它是通过对 A 线或 B 扫描图像之间的互相关矩阵进行五倍上采样来实现的。由于运动校正算法只将采集到的数据作为先验，它可以在输入 B 扫描时立即处理，因此可以嵌入到采集程序中，从而在数据采集过程中进行运动校正。此外，该算法还通过人体皮肤的实验数据进行了验证。结果表明，亚像素运动校正后的图像在视觉上有明显改善，校正后相邻B扫描图像之间的结构相似性指数测量（SSIM）和峰值信噪比（PSNR）提高了31.6%与未校正图像相比为 47.7%。总而言之，所提出的算法可以使其在准确性和可靠性方面具有鲁棒性，并将帮助 PAD 实现其临床承诺。该算法通过人体皮肤的实验数据进行验证。结果表明，亚像素运动校正后的图像在视觉上有明显改善，校正后相邻B扫描图像之间的结构相似性指数测量（SSIM）和峰值信噪比（PSNR）提高了31.6%与未校正图像相比为 47.7%。总而言之，所提出的算法可以使其在准确性和可靠性方面具有鲁棒性，并将帮助 PAD 实现其临床承诺。该算法通过人体皮肤的实验数据进行验证。结果表明，亚像素运动校正后的图像在视觉上有明显改善，校正后相邻B扫描图像之间的结构相似性指数测量（SSIM）和峰值信噪比（PSNR）提高了31.6%与未校正图像相比为 47.7%。总而言之，所提出的算法可以使其在准确性和可靠性方面具有鲁棒性，并将帮助 PAD 实现其临床承诺。7% 与未校正的图像相比。总而言之，所提出的算法可以使其在准确性和可靠性方面具有鲁棒性，并将帮助 PAD 实现其临床承诺。7% 与未校正的图像相比。总而言之，所提出的算法可以使其在准确性和可靠性方面具有鲁棒性，并将帮助 PAD 实现其临床承诺。