基于深度学习病原微生物形态学检测方法的研究现状及展望

Research Status and Prospects of Morphological Detection Methods for Pathogenic Microorganisms Based on Deep Learning

病原微生物导致的传染病严重威胁人类健康。目前有多种微生物的分析方法,如酶联免疫吸附试验、聚合酶链式反应以及基于显微镜的形态学检测,其中形态学检测方法具有成本低和准确性高的特点。随着计算机技术的发展以及人工智能(Artificial Intelligence,AI)在生物医学领域应用的不断探索,使显微镜下微生物图像的自动形态识别成为可能。本文旨在对近年来国内外基于AI的形态学诊断技术在病毒、细菌、寄生虫和真菌的应用进行了分析,讨论了现有研究存在的不足和挑战,并进一步提出了新的研究思路:利用AI、微型化、自动控制等技术实现全自动便携化高致病微生物分析仪的研发,该设备将用于病原微生物实时检测,对生物安全预警具有重要意义。

Infectious diseases caused by pathogenic microorganisms seriously threaten human health.At present,there are a variety of microbial analysis methods,such as enzyme-linked immunosorbent assay,polymerase chain reaction and microscopebased morphological detection methods,among which the morphological detection method has the characteristics of low cost and high accuracy.With the development of computer technology and the continuous exploration of the application of artificial intelligence(AI)in the field of biomedicine,automatic morphological recognition of microbiological images under the microscope has become possible.This paper aims to analyze the application of morphological diagnosis techniques based on AI in viruses,bacteria,parasites and fungi at home and abroad in recent years,and to discuss shortcomings and challenges of the existing research,to further propose a new research idea:the development of a fully automatic portable highly pathogenic microorganism analyzer using AI,miniaturization,automatic control and other technologies.The device will be used for real-time detection of pathogenic microorganisms,which is of great significance for biosafety early warning.