In situ biological particle analyzer based on digital inline holography
In situ biological particle analyzer based on digital inline holography
复制标题
DOI：
10.1002/bit.28338
复制
发表时间：
2023-01
影响因子：
3.8
通讯作者：
Delaney Sanborn;Ruichen He;Lei Feng;Jiarong Hong
中科院分区：
文献类型：
--
作者：
Delaney Sanborn;Ruichen He;Lei Feng;Jiarong Hong
获得生物微粒的现场测量对于科学研究和许多工业应用(例如，及早发现有害的藻华、在发酵过程中监测酵母)都是至关重要的。然而，现有的方法局限于以足够的准确性和信息提供对这些颗粒的及时诊断。在这里，我们介绍了一种使用机器学习(ML)辅助数字在线全息(DIH)进行实时、原位分析的新方法。我们的ML模型使用定制的YOLOv5架构，专门用于检测和分类微小的生物颗粒。我们证明了我们的方法在分析10种浮游生物时的有效性，与以前的方法相比，我们的方法具有相当高的精度和显著的处理时间。我们还应用我们的方法区分了四种代谢状态下的酵母细胞和来自两个菌株的酵母细胞。我们的结果表明，所提出的方法可以准确地检测和区分与代谢状态和菌株相关的细胞和亚细胞特征。这项研究展示了ML驱动的DIH方法作为一种灵敏和通用的诊断工具的潜力，用于实时、原位分析生物和非生物颗粒。这种方法可以很容易地以分布式方式部署，用于工业规模的科学研究和制造。
Obtaining in situ measurements of biological microparticles is crucial for both scientific research and numerous industrial applications (e.g., early detection of harmful algal blooms, monitoring yeast during fermentation). However, existing methods are limited to offer timely diagnostics of these particles with sufficient accuracy and information. Here, we introduce a novel method for real‐time, in situ analysis using machine learning (ML)‐assisted digital inline holography (DIH). Our ML model uses a customized YOLOv5 architecture specialized for the detection and classification of small biological particles. We demonstrate the effectiveness of our method in the analysis of 10 plankton species with equivalent high accuracy and significantly reduced processing time compared to previous methods. We also applied our method to differentiate yeast cells under four metabolic states and from two strains. Our results show that the proposed method can accurately detect and differentiate cellular and subcellular features related to metabolic states and strains. This study demonstrates the potential of ML‐driven DIH approach as a sensitive and versatile diagnostic tool for real‐time, in situ analysis of both biotic and abiotic particles. This method can be readily deployed in a distributive manner for scientific research and manufacturing on an industrial scale.