Su Xuesan, Wang Yaonan, Mao Jianxu, Chen Yurong, Yin ATing, Zhao Bingrui, Zhang Hui, Liu Min
National Engineering Laboratory of Robot Visual Perception and Control Technology, Hunan University, Changsha, 410082 Hunan People's Republic of China.
J Intell Robot Syst. 2022;105(4):75. doi: 10.1007/s10846-022-01602-7. Epub 2022 Jul 22.
The quality and safety of medicinal products are related to patients' lives and health. Therefore, quality inspection takes a key role in the pharmaceutical industry. Most of the previous solutions are based on machine vision, however, their performance is limited by the RGB sensor. The pharmaceutical visual inspection robot combined with hyperspectral imaging technology is becoming a new trend in the high-end medical quality inspection process since the hyperspectral data can provide spectral information with spatial knowledge. Yet, there is no comprehensive review about hyperspectral imaging-based medicinal products inspection. This paper focuses on the pivotal pharmaceutical applications, including counterfeit drugs detection, active component analysis of tables, and quality testing of herbal medicines and other medical materials. We discuss the technology and hardware of Raman spectroscopy and hyperspectral imaging, firstly. Furthermore, we review these technologies in pharmaceutical scenarios. Finally, the development tendency and prospect of hyperspectral imaging technology-based robots in the field of pharmaceutical quality inspection is summarized.
药品的质量和安全关乎患者的生命与健康。因此，质量检验在制药行业中起着关键作用。以往的大多数解决方案基于机器视觉，然而，它们的性能受到RGB传感器的限制。结合高光谱成像技术的药品视觉检测机器人正成为高端医疗质量检测过程中的新趋势，因为高光谱数据能够提供具有空间信息的光谱信息。然而, 目前尚无关于基于高光谱成像的药品检测的全面综述。本文重点关注关键的制药应用，包括假药检测、片剂活性成分分析以及草药和其他医疗材料的质量检测。我们首先讨论拉曼光谱和高光谱成像的技术及硬件。此外，我们对这些技术在制药场景中的应用进行综述。最后，总结了基于高光谱成像技术的机器人在药品质量检测领域的发展趋势和前景。
