A Deep-Learning Based System for Rapid Genus Identification of Pathogens under Hyperspectral Microscopic Images
文献类型:期刊论文
作者 | Tao, Chenglong3,4,5; Du, Jian3,5; Tang, Yingxin2; Wang, Junjie4,5; Dong, Ke1; Yang, Ming1; Hu, Bingliang3,5; Zhang, Zhoufeng3,5 |
刊名 | CELLS |
出版日期 | 2022-07 |
卷号 | 11期号:14 |
ISSN号 | 2073-4409 |
关键词 | infectious pathogens hyperspectral microscopy bacteria identification artificial intelligence imaging genus spectral characteristics |
DOI | 10.3390/cells11142237 |
产权排序 | 1 |
英文摘要 | Infectious diseases have always been a major threat to the survival of humanity. Additionally, they bring an enormous economic burden to society. The conventional methods for bacteria identification are expensive, time-consuming and laborious. Therefore, it is of great importance to automatically rapidly identify pathogenic bacteria in a short time. Here, we constructed an AI-assisted system for automating rapid bacteria genus identification, combining the hyperspectral microscopic technology and a deep-learning-based algorithm Buffer Net. After being trained and validated in the self-built dataset, which consists of 11 genera with over 130,000 hyperspectral images, the accuracy of the algorithm could achieve 94.9%, which outperformed 1D-CNN, 2D-CNN and 3D-ResNet. The AI-assisted system we developed has great potential in assisting clinicians in identifying pathogenic bacteria at the single-cell level with high accuracy in a cheap, rapid and automatic way. Since the AI-assisted system can identify the pathogenic genus rapidly (about 30 s per hyperspectral microscopic image) at the single-cell level, it can shorten the time or even eliminate the demand for cultivating. Additionally, the system is user-friendly for novices. |
语种 | 英语 |
出版者 | MDPI |
WOS记录号 | WOS:000833722700001 |
源URL | [http://ir.opt.ac.cn/handle/181661/96084] |
专题 | 西安光学精密机械研究所_光学影像学习与分析中心 |
通讯作者 | Hu, Bingliang; Zhang, Zhoufeng |
作者单位 | 1.Air Force Mil Med Univ, Affiliated Hosp 2, Xian 710119, Peoples R China 2.Independent Researcher, Changsha 410000, China; 3.Key Lab Biomed Spect Xian, Xian 710119, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China |
推荐引用方式 GB/T 7714 | Tao, Chenglong,Du, Jian,Tang, Yingxin,et al. A Deep-Learning Based System for Rapid Genus Identification of Pathogens under Hyperspectral Microscopic Images[J]. CELLS,2022,11(14). |
APA | Tao, Chenglong.,Du, Jian.,Tang, Yingxin.,Wang, Junjie.,Dong, Ke.,...&Zhang, Zhoufeng.(2022).A Deep-Learning Based System for Rapid Genus Identification of Pathogens under Hyperspectral Microscopic Images.CELLS,11(14). |
MLA | Tao, Chenglong,et al."A Deep-Learning Based System for Rapid Genus Identification of Pathogens under Hyperspectral Microscopic Images".CELLS 11.14(2022). |
入库方式: OAI收割
来源:西安光学精密机械研究所
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