Shanghai Key Laboratory of Forensic Medicine, Key Laboratory of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai 200063, China.
School of Forensic Medicine, Shanxi Medical University, Taiyuan 030001, China.
Fa Yi Xue Za Zhi. 2022 Feb 25;38(1):14-19. doi: 10.12116/j.issn.1004-5619.2021.410404.
Diatom test is the main laboratory test method in the diagnosis of drowning in forensic medicine. It plays an important role in differentiating the antemortem drowning from the postmortem drowning and inferring drowning site. Artificial intelligence (AI) automatic diatom test is a technological innovation in forensic drowning diagnosis which is based on morphological characteristics of diatom, the application of AI algorithm to automatic identification and classification of diatom in tissues and organs. This paper discusses the morphological diatom test methods and reviews the research progress of automatic diatom recognition and classification involving AI algorithms. AI deep learning algorithm can assist diatom testing to obtain objective, accurate, and efficient qualitative and quantitative analysis results, which is expected to become a new direction of diatom testing research in the drowning of forensic medicine in the future.
硅藻检验是法医学诊断溺死的主要实验室检验方法。它在鉴别生前溺死与死后溺死以及推断溺死地点方面发挥着重要作用。人工智能(AI)自动硅藻检验是法医学溺死诊断中的一项技术创新,它基于硅藻的形态特征,应用 AI 算法对组织和器官中的硅藻进行自动识别和分类。本文讨论了形态硅藻检验方法,并综述了涉及 AI 算法的自动硅藻识别和分类的研究进展。AI 深度学习算法可以辅助硅藻检验,获得客观、准确、高效的定性和定量分析结果,有望成为未来法医学溺死硅藻检验研究的新方向。