Mid-infrared multispectral lensless imaging for wide-field and label-free microbial identification

Joel Legaludec, M. Dupoy, V. Rebuffel, P. Marcoux
{"title":"Mid-infrared multispectral lensless imaging for wide-field and label-free microbial identification","authors":"Joel Legaludec, M. Dupoy, V. Rebuffel, P. Marcoux","doi":"10.1117/12.2557502","DOIUrl":null,"url":null,"abstract":"Microbial identification is a critical process aiming at identifying the species contained in a biological sample, with applications in healthcare, industry or even national security. Traditionally, this process relies either on MALDI-TOF mass spectroscopy, on biochemical tests and on the observation of the morphology of colonies after growth on a Petri dish. Here is presented an innovative method for label-free optical identification of pathogens, based on the multispectral infrared imaging of colonies. This lensless imaging technique enables a high-throughput analysis and wide-field analysis of agar plates. It could yield very high correct identification rates as it relies on an optical fingerprint gathering both spectroscopic and morphologic features. The setup consists of a Quantum Cascade Lasers light source and an imager, a square 2.72 by 2.72 mm uncooled bolometer array. Microorganisms to be analyzed are streaked on a porous growth support compatible with infrared imaging, laid on top of an agar plate for incubation. When imaging is performed, growth support is put in close contact with the imaging sensor and illuminated at different wavelengths. After acquisition, an image descriptor based on spectral and morphological features is extracted for each microbial colony. Supervised classification is finally performed with a Support Vector Machine algorithm and tested with tenfold cross-validation. A first database collecting 1012 multispectral images of colonies belonging to five different species has already been acquired with this system, resulting in a correct identification rate of 92%. For these experiments, multispectral images are acquired at nine different wavelengths, between 5.6 and 8 µm. Considering the optimization possibilities of the image descriptors currently used and the ongoing development of the uncooled bolometers technology, these very first results are promising and could be dramatically improved with further experiments. Thereby, mid-infrared multispectral lensless imaging has the potential to become a fast and precise Petri dish analysis technology.","PeriodicalId":146152,"journal":{"name":"Biomedical Spectroscopy, Microscopy, and Imaging","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomedical Spectroscopy, Microscopy, and Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2557502","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Microbial identification is a critical process aiming at identifying the species contained in a biological sample, with applications in healthcare, industry or even national security. Traditionally, this process relies either on MALDI-TOF mass spectroscopy, on biochemical tests and on the observation of the morphology of colonies after growth on a Petri dish. Here is presented an innovative method for label-free optical identification of pathogens, based on the multispectral infrared imaging of colonies. This lensless imaging technique enables a high-throughput analysis and wide-field analysis of agar plates. It could yield very high correct identification rates as it relies on an optical fingerprint gathering both spectroscopic and morphologic features. The setup consists of a Quantum Cascade Lasers light source and an imager, a square 2.72 by 2.72 mm uncooled bolometer array. Microorganisms to be analyzed are streaked on a porous growth support compatible with infrared imaging, laid on top of an agar plate for incubation. When imaging is performed, growth support is put in close contact with the imaging sensor and illuminated at different wavelengths. After acquisition, an image descriptor based on spectral and morphological features is extracted for each microbial colony. Supervised classification is finally performed with a Support Vector Machine algorithm and tested with tenfold cross-validation. A first database collecting 1012 multispectral images of colonies belonging to five different species has already been acquired with this system, resulting in a correct identification rate of 92%. For these experiments, multispectral images are acquired at nine different wavelengths, between 5.6 and 8 µm. Considering the optimization possibilities of the image descriptors currently used and the ongoing development of the uncooled bolometers technology, these very first results are promising and could be dramatically improved with further experiments. Thereby, mid-infrared multispectral lensless imaging has the potential to become a fast and precise Petri dish analysis technology.
用于宽视场和无标签微生物鉴定的中红外多光谱无透镜成像
微生物鉴定是一项关键的过程,旨在鉴定生物样品中所含的物种,在医疗保健、工业甚至国家安全方面都有应用。传统上,这一过程依赖于MALDI-TOF质谱、生化测试和在培养皿中生长后对菌落形态的观察。本文提出了一种基于菌落多光谱红外成像的病原菌无标记光学鉴定方法。这种无透镜成像技术使琼脂板的高通量分析和宽视场分析成为可能。它可以产生非常高的正确识别率,因为它依赖于光指纹收集光谱和形态特征。该装置由一个量子级联激光器光源和一个成像仪组成,成像仪是一个2.72 × 2.72毫米的方形非冷却测热计阵列。待分析的微生物在与红外成像兼容的多孔生长支架上划线,放在琼脂板上孵育。当进行成像时,生长支架与成像传感器紧密接触,并以不同的波长照射。采集完成后,对每个微生物菌落提取基于光谱和形态特征的图像描述符。最后使用支持向量机算法进行监督分类,并进行十倍交叉验证。该系统已建立了第一个数据库,收集了5个不同物种的1012个菌落的多光谱图像,正确率达到92%。在这些实验中,在5.6到8µm之间的9个不同波长处获得了多光谱图像。考虑到目前使用的图像描述符的优化可能性和非冷却热计技术的持续发展,这些最初的结果是有希望的,并且可以通过进一步的实验大大改进。因此,中红外多光谱无透镜成像有潜力成为一种快速、精确的培养皿分析技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信