Motion Quantification and Automated Correction in Clinical RSOM
Motion Quantification and Automated Correction in Clinical RSOM
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DOI：
10.1109/tmi.2018.2883154
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发表时间：
2019-06-01
影响因子：
10.6
通讯作者：
Ntziachristos, Vasilis
中科院分区：
文献类型：
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作者：
Aguirre, Juan;Berezhnoi, Andrei;Ntziachristos, Vasilis
光栅扫描光声介观镜 (RSOM) 提供了对皮肤病理生理学的高分辨率非侵入性见解，这为皮肤病学和其他领域的疾病诊断和监测带来了希望。然而，RSOM 很容易受到皮肤垂直运动的影响，这可能取决于被成像的身体部位。运动校正算法已经被提出，但它们并不是完全自动化的，它们依赖于可能无法成功执行的解剖分割预处理步骤，并且它们不是特定于站点的。在这里，我们首次确定了影响 RSOM 的身体不同部位的微米垂直皮肤位移的大小。运动的量化使我们能够开发出针对特定地点的校正算法。该算法是完全自动化的，不需要事先的解剖信息。我们发现垂直运动的幅度很大程度上取决于成像部位，并且是由呼吸、心跳和动脉搏动引起的。所开发的算法使每个测试站点的重建图像的信噪比提高了 2 倍以上。提出有效的自动运动校正算法为实现 RSOM 的全部临床潜力铺平了道路。
Raster-scan optoacoustic mesoscopy (RSOM) offers high-resolution non-invasive insights into skin pathophysiology, which holds promise for disease diagnosis and monitoring in dermatology and other fields. However, RSOM is quite vulnerable to verticalmotion of the skin, which can depend on the part of the body being imaged. Motion correction algorithms have already been proposed, but they are not fully automated, they depend on anatomical segmentation pre-processing steps that might not be performed successfully, and they are not site-specific. Here, we determined for the first time the magnitude of themicrometric vertical skin displacements at different sites on the body that affect RSOM. The quantification of motion allowed us to develop a site-specific correction algorithm. The algorithm is fully automated and does not need prior anatomical information. We found that the magnitude of the vertical motion depends strongly on the site of imaging and is caused by breathing, heart beating, and arterial pulsation. The developed algorithm resulted in more than 2-fold improvement in the signal-to-noise ratio of the reconstructed images at every site tested. Proposing an effective automatedmotion correction algorithm paves the way for realizing the full clinical potential of RSOM.