Reconstruction of the absorption spectrum of an object spot from the colour values of the corresponding pixel(s) in its digital image: the challenge of algal colours

Coltelli, Primo; Barsanti, Laura; Evangelista, Valtere; Frassanito, Anna Maria; Gualtieri, Paolo

doi:10.1111/jmi.12445

Cited by 5 publications

(7 citation statements)

References 23 publications

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“…To understand whether these differences correspond to different exclusion mechanisms for heavy metals (chromium in our case), and if these algae can be use as probes or bioremediators (Juarez et al, ; Rodriguez et al, ), we used in vivo microspectroscopy to monitor the degradation of the chlorophylls with the consequent formation of phaeophytins, the magnesium‐free derivative of chlorophylls, inside single cells. The spectroscopic contribution of each pigment to the absorption spectrum envelop was calculated by an unsupervised statistical estimation in a fully Bayesian setting,that is each component pigment is isolated from a set of known mixtures of the pigments (Bell & Sejnowski, ; Cichocki & Amari, ; Coltelli et al, ).…”

Section: Resultsmentioning

confidence: 99%

“…For correct color acquisition, the CCD camera undergoes color calibration in three steps: White balancing, Gamma correction, and Matrix correction (Coltelli, Barsanti, Evangelista, Frassanito, & Gualtieri, ). For integrated density determination, quasi‐monochromatic images are acquired by means of 1″ interferential filters with 10 nm bandwidth (Balzers, Germany) at about 10 nm wavelength interval from 400 nm to 700 nm.…”

Section: Methodsmentioning

confidence: 99%

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Algae through the looking glass

Coltelli

Barsanti

Evangelista

et al. 2017

Microscopy Res & Technique

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Microalgae are one of the most suitable subjects for testing the potentiality of light microscopy and image analysis, because of the size of single cells, their endogenous chromaticity, and their metabolic and physiological characteristics. Microscope observations and image analysis can use microalgal cells from lab cultures or collected from water bodies as model to investigate metabolic processes, behavior/reaction of cells under chemical or photic stimuli, and dynamics of population in the natural environment in response to changing conditions. In this paper we will describe the original microscope we set up together with the image processing techniques we improved to deal with these topics. Our system detects and recognizes in-focus cells, extracts their features, measures cell concentration in multi-algal samples, reconstructs swimming cell tracks, monitors metabolic processes, and measure absorption and fluorescent spectra of subcellular compartments. It can be used as digital microscopy station for algal cell biology and behavioral studies, and field analysis applications.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Algae through the looking glass

Coltelli

Barsanti

Evangelista

et al. 2017

Microscopy Res & Technique

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“…In the experiment, an accuracy of 98.6% is obtained on a set of 53,869 images of 23 different microalgae classes. As an extension of the works above Coltelli et al (2016), colour information is additionally extracted and used to reconstruct the absorption spectrum of an object spot from the colour values of the corresponding pixels in its digital image.…”

Section: Original Methodsmentioning

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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“…In the case of cellular compartments containing different pigments as the chloroplasts (chlorophylls, carotenoids and phycobiliproteins), the relative contribution of the individual pigments to the absorption spectra is often difficult to identify and quantify, since the ability to discriminate among the different contributions depends upon the robustness of the chosen technique. The curve-fitting routine, which relies upon templates of the absorption spectra of pigments previously measured in the natural environment, has proved to be an efficient and reliable method, as shown by Coltelli et al (2016) [16].…”

Section: Microspectrophotometry 21 General Descriptionmentioning

confidence: 99%

“…This example has been selected to demonstrate the effectiveness of the spectral envelop decomposition developed by Coltelli et al, (2016) [16].…”

Section: Experimental Example 2: Which Is the Prey?mentioning

confidence: 99%

Advanced Microscopy Techniques for Molecular Biophysics

Barsanti

Birindelli

Sbrana

et al. 2023

IJMS

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Though microscopy is most often intended as a technique for providing qualitative assessment of cellular and subcellular properties, when coupled with other instruments such as wavelength selectors, lasers, photoelectric devices and computers, it can perform a wide variety of quantitative measurements, which are demanding in establishing relationships between the properties and structures of biological material in all their spatial and temporal complexities. These combinations of instruments are a powerful approach to improve non-destructive investigations of cellular and subcellular properties (both physical and chemical) at a macromolecular scale resolution. Since many subcellular compartments in living cells are characterized by structurally organized molecules, this review deals with three advanced microscopy techniques well-suited for these kind of investigations, i.e., microspectrophotometry (MSP), super-resolution localization microscopy (SRLM) and holotomographic microscopy (HTM). These techniques can achieve an insight view into the role intracellular molecular organizations such as photoreceptive and photosynthetic structures and lipid bodies play in many cellular processes as well as their biophysical properties. Microspectrophotometry uses a set-up based on the combination of a wide-field microscope and a polychromator, which allows the measurement of spectroscopic features such as absorption spectra. Super resolution localization microscopy combines dedicated optics and sophisticated software algorithms to overcome the diffraction limit of light and allow the visualization of subcellular structures and dynamics in greater detail with respect to conventional optical microscopy. Holotomographic microscopy combines holography and tomography techniques into a single microscopy set-up, and allows 3D reconstruction by means of the phase separation of biomolecule condensates. This review is organized in sections, which for each technique describe some general aspects, a peculiar theoretical aspect, a specific experimental configuration and examples of applications (fish and algae photoreceptors, single labeled proteins and endocellular aggregates of lipids).

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Reconstruction of the absorption spectrum of an object spot from the colour values of the corresponding pixel(s) in its digital image: the challenge of algal colours

Cited by 5 publications

References 23 publications

Algae through the looking glass

Algae through the looking glass

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

Advanced Microscopy Techniques for Molecular Biophysics

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