A Method for Rapid Analysis of Biofilm Morphology and Coverage on Glass and Polished and Brushed Stainless Steel

Lomander, Andrea; Schreuders, Paul; Russek‐Cohen, Estelle; Ali, Laila

doi:10.13031/2013.8506

Cited by 7 publications

(8 citation statements)

References 30 publications

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“…In [ 62 , 63 ], biofilm is applied for reconstruction and quantification of bacteria biovolume. First, a median filter [ 62 ] and contrast stretching [ 63 ] are applied for noise reduction, and then the image contrast is enhanced by using histogram stretching. After that, the method of histogram equalization and a high pass filter [ 63 ] is applied to enhance images.…”

Section: Microorganism Biovolume Measurement Methodsmentioning

confidence: 99%

A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements

Zhang

Rahaman

et al. 2022

Arch Computat Methods Eng

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With the acceleration of urbanization and living standards, microorganisms play an increasingly important role in industrial production, bio-technique, and food safety testing. Microorganism biovolume measurements are one of the essential parts of microbial analysis. However, traditional manual measurement methods are time-consuming and challenging to measure the characteristics precisely. With the development of digital image processing techniques, the characteristics of the microbial population can be detected and quantified. The applications of the microorganism biovolume measurement method have developed since the 1980s. More than 62 articles are reviewed in this study, and the articles are grouped by digital image analysis methods with time. This study has high research significance and application value, which can be referred to as microbial researchers to comprehensively understand microorganism biovolume measurements using digital image analysis methods and potential applications.

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Section: Microorganism Biovolume Measurement Methodsmentioning

confidence: 99%

A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements

Zhang

Rahaman

et al. 2022

Arch Computat Methods Eng

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“…In [78,92], biofilm is applied for reconstruction and quantification of bacteria biovolume. First, a median filter [78] and contrast stretching [92] are applied for noise reduction, and then the image contrast is enhanced by using histogram stretching. After that, the method of histogram equalization and a high pass filter [92] is applied to enhance images.…”

Section: Bacteria Measurement Methods Based On Gray Level Histogrammentioning

confidence: 99%

“…After that, the method of histogram equalization and a high pass filter [92] is applied to enhance images. In [78], the dead biofilm patches are eliminated by comparing the patch morphology with substrate morphology, and three metrics are then computed for the individual biofilm patches: patch area, patch perimeter, and circularity, which can be applied for bacteria colony biovolume measurement. The result shows that the patch morphology is useful for investigating the relationships between surface morphology with biofilm growth and determining the surface morphology and biofilm shape.…”

Section: Bacteria Measurement Methods Based On Gray Level Histogrammentioning

confidence: 99%

A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements

Zhang¹,

Li²,

Rahaman³

et al. 2022

Preprint

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With the acceleration of urbanization and living standards, microorganisms play increasingly important roles in industrial production, bio-technique, and food safety testing. Microorganism biovolume measurements are one of the essential parts of microbial analysis. However, traditional manual measurement methods are time-consuming and challenging to measure the characteristics precisely. With the development of digital image processing techniques, the characteristics of the microbial population can be detected and quantified. The changing trend can be adjusted in time and provided a basis for the improvement. The applications of the microorganism biovolume measurement method have developed since the 1980s. More than 60 articles are reviewed in this study, and the articles are grouped by digital image segmentation methods with periods. This study has high research significance and application value, which can be referred to microbial researchers to have a comprehensive understanding of microorganism biovolume measurements using digital image analysis methods and potential applications.

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“…In Lomander et al (2002), a binary classification approach is introduced to distinguish normal and damaged bacteria, where image enhancing is firstly applied, then shape features are extracted, finally decision values are used to recognise different types.…”

Section: Overview Of Im Classificationmentioning

confidence: 99%

“…Beneficial AMs can help farmers to increase the agricultural yields, for Shabtai et al (1996), Ronen et al (2002) IM 1998 Gerlach SR et al Gerlach et al (1998) IM 2001 Lee MS et al Lee et al (2001) IM 2002 Lomander A et al Lomander et al (2002) IM 2002 Park JP et al Park et al (2002) IM 2007 Lecault V et al Lecault et al (2007) IM 2011 Yu B et al Yu et al (2011) MM 1992 Reichl U et al Reichl et al (1992) MM 1994 Pichon D et al Pichon et al (1994) MM 1996 Oh B et al Oh et al (1996) MM 1997 Tamura S et al Tamura et al (1997) MM 1998 Veropoulos K et al Veropoulos et al (1998) MM 1998 Wit P et al Wit and Busscher (1998) MM 1999 Kay JW et al Kay et al (1999) MM 2000 Khutlang R et al Khutlang et al (2009Khutlang et al ( , 2010a MM 2011 Rulaningtyas R et al Rulaningtyas et al (2011) MM 2011 Pangilinan C et al Pangilinan et al (2011) MM 2011-2012Osman MK et al Osman et al (2011a, b, 2012 MM 2012 Chang J et al Chang et al (2012b) MM 2012-2016 Priya E et al Priya et al (2012), Srinivasan (2015a, b, 2016) Culverhouse et al (1994Culverhouse et al ( , 1996Culverhouse et al ( , 2000Culverhouse et al ( , 2003Culverhouse et al ( , 2006a WM 1995 Thiel S et al Thiel and Davies (1995), …”

Section: Application Domain Introductionmentioning

confidence: 99%

A survey for the applications of content-based microscopic image analysis in microorganism classification domains

Wang

2017

Artif Intell Rev

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Microorganisms such as protozoa and bacteria play very important roles in many practical domains, like agriculture, industry and medicine. To explore functions of different categories of microorganisms is a fundamental work in biological studies, which can assist biologists and related scientists to get to know more properties, habits and characteristics of these tiny but obbligato living beings. However, taxonomy of microorganisms (microorganism classification) is traditionally investigated through morphological, chemical or physical analysis, which is time and money consuming. In order to overcome this, since the 1970s innovative content-based microscopic image analysis (CBMIA) approaches are introduced to microbiological fields. CBMIA methods classify microorganisms into different categories using multiple artificial intelligence approaches, such as machine vision, pattern recognition and machine learning algorithms. Furthermore, because CBMIA approaches are semior full-automatic computer-based methods, they are very efficient and labour cost saving, supporting a technical feasibility for microorganism classification in our current big data age. In this article, we review the development history of microorganism classification using CBMIA approaches with two crossed pipelines. In the first pipeline, all related works are grouped by their corresponding microorganism application domains. By this pipeline, it is easy for microbiologists to have an insight into each special application domain and find their interested applied CBMIA techniques. In the second pipeline, the related works in each application domain are reviewed by time periods. Using this pipeline, computer scientists can see the dynamic of technological development clearly and keep up with the future devel-

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A Method for Rapid Analysis of Biofilm Morphology and Coverage on Glass and Polished and Brushed Stainless Steel

Cited by 7 publications

References 30 publications

A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements

A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements

A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements

A survey for the applications of content-based microscopic image analysis in microorganism classification domains

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