Objectification of evaluation criteria in microscopic agglutination test using deep learning

IF 1.7 4区生物学 Q4 BIOCHEMICAL RESEARCH METHODS

Journal of microbiological methods Pub Date : 2024-05-14 DOI:10.1016/j.mimet.2024.106955

Risa Nakano , Yuji Oyamada , Ryo Ozuru , Michinobu Yoshimura , Kenji Hiromatsu

引用次数: 0

Abstract

We aim to objectify the evaluation criteria of agglutination rate estimation in the Microscopic Agglutination Test (MAT). This study proposes a deep learning method that extracts free leptospires from dark-field microscopic images and calculates the agglutination rate. The experiments show the effect of objectification with real pictures.

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利用深度学习实现显微凝集试验评价标准的客观化

我们旨在为显微镜凝集试验（MAT）中凝集率估计的评价标准制定客观标准。本研究提出了一种深度学习方法，可从暗视野显微图像中提取游离钩端螺旋体并计算凝集率。实验显示了真实图片的物化效果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of microbiological methods 生物-生化研究方法

CiteScore

4.30

自引率

4.50%

发文量

151

审稿时长

29 days

期刊介绍： The Journal of Microbiological Methods publishes scholarly and original articles, notes and review articles. These articles must include novel and/or state-of-the-art methods, or significant improvements to existing methods. Novel and innovative applications of current methods that are validated and useful will also be published. JMM strives for scholarship, innovation and excellence. This demands scientific rigour, the best available methods and technologies, correctly replicated experiments/tests, the inclusion of proper controls, calibrations, and the correct statistical analysis. The presentation of the data must support the interpretation of the method/approach. All aspects of microbiology are covered, except virology. These include agricultural microbiology, applied and environmental microbiology, bioassays, bioinformatics, biotechnology, biochemical microbiology, clinical microbiology, diagnostics, food monitoring and quality control microbiology, microbial genetics and genomics, geomicrobiology, microbiome methods regardless of habitat, high through-put sequencing methods and analysis, microbial pathogenesis and host responses, metabolomics, metagenomics, metaproteomics, microbial ecology and diversity, microbial physiology, microbial ultra-structure, microscopic and imaging methods, molecular microbiology, mycology, novel mathematical microbiology and modelling, parasitology, plant-microbe interactions, protein markers/profiles, proteomics, pyrosequencing, public health microbiology, radioisotopes applied to microbiology, robotics applied to microbiological methods,rumen microbiology, microbiological methods for space missions and extreme environments, sampling methods and samplers, soil and sediment microbiology, transcriptomics, veterinary microbiology, sero-diagnostics and typing/identification.