scholarly journals Use of Hyperspectral/Multispectral Imaging in Gastroenterology. Shedding Some–Different–Light into the Dark

2019 ◽  
Vol 8 (1) ◽  
pp. 36 ◽  
Author(s):  
Samuel Ortega ◽  
Himar Fabelo ◽  
Dimitris Iakovidis ◽  
Anastasios Koulaouzidis ◽  
Gustavo Callico
Keyword(s):  
Multispectral Imaging ◽  
Geological Mapping ◽  
Human Vision ◽  
Pollution Monitoring ◽  
Electromagnetic Spectrum ◽  
Spectral Techniques ◽  
Non Invasive ◽  
Different Response ◽  
New Diagnosis ◽  
Optical Properties Of Tissue

Hyperspectral/Multispectral imaging (HSI/MSI) technologies are able to sample from tens to hundreds of spectral channels within the electromagnetic spectrum, exceeding the capabilities of human vision. These spectral techniques are based on the principle that every material has a different response (reflection and absorption) to different wavelengths. Thereby, this technology facilitates the discrimination between different materials. HSI has demonstrated good discrimination capabilities for materials in fields, for instance, remote sensing, pollution monitoring, field surveillance, food quality, agriculture, astronomy, geological mapping, and currently, also in medicine. HSI technology allows tissue observation beyond the limitations of the human eye. Moreover, many researchers are using HSI as a new diagnosis tool to analyze optical properties of tissue. Recently, HSI has shown good performance in identifying human diseases in a non-invasive manner. In this paper, we show the potential use of these technologies in the medical domain, with emphasis in the current advances in gastroenterology. The main aim of this review is to provide an overview of contemporary concepts regarding HSI technology together with state-of-art systems and applications in gastroenterology. Finally, we discuss the current limitations and upcoming trends of HSI in gastroenterology.

Exploiting multispectral imaging for non-invasive contamination assessment and mapping of meat samples

Talanta ◽  
2016 ◽  
Vol 161 ◽  
pp. 606-614 ◽  
Author(s):  
Panagiotis Tsakanikas ◽  
Dimitris Pavlidis ◽  
Efstathios Panagou ◽  
George-John Nychas
Keyword(s):  
Multispectral Imaging ◽  
Contamination Assessment ◽  
Non Invasive ◽  
Meat Samples

scholarly journals Prediction of Optical and Non-Optical Water Quality Parameters in Oligotrophic and Eutrophic Aquatic Systems Using a Small Unmanned Aerial System

Drones ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 1 ◽  
Author(s):  
Juan G. Arango ◽  
Robert W. Nairn
Keyword(s):  
Water Quality ◽  
Multispectral Imaging ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
P Value ◽  
Unmanned Aerial System ◽  
Electromagnetic Spectrum ◽  
Linear Regression Models ◽  
Chl A ◽  
Average Value

The purpose of this study was to create different statistically reliable predictive algorithms for trophic state or water quality for optical (total suspended solids (TSS), Secchi disk depth (SDD), and chlorophyll-a (Chl-a)) and non-optical (total phosphorus (TP) and total nitrogen (TN)) water quality variables or indicators in an oligotrophic system (Grand River Dam Authority (GRDA) Duck Creek Nursery Ponds) and a eutrophic system (City of Commerce, Oklahoma, Wastewater Lagoons) using remote sensing images from a small unmanned aerial system (sUAS) equipped with a multispectral imaging sensor. To develop these algorithms, two sets of data were acquired: (1) In-situ water quality measurements and (2) the spectral reflectance values from sUAS imagery. Reflectance values for each band were extracted under three scenarios: (1) Value to point extraction, (2) average value extraction around the stations, and (3) point extraction using kriged surfaces. Results indicate that multiple variable linear regression models in the visible portion of the electromagnetic spectrum best describe the relationship between TSS (R2 = 0.99, p-value = <0.01), SDD (R2 = 0.88, p-value = <0.01), Chl-a (R2 = 0.85, p-value = <0.01), TP (R2 = 0.98, p-value = <0.01) and TN (R2 = 0.98, p-value = <0.01). In addition, this study concluded that ordinary kriging does not improve the fit between the different water quality parameters and reflectance values.

scholarly journals Recent Applications of Multispectral Imaging in Seed Phenotyping and Quality Monitoring—An Overview

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1090 ◽  
Author(s):  
Gamal ElMasry ◽  
Nasser Mandour ◽  
Salim Al-Rejaie ◽  
Etienne Belin ◽  
David Rousseau
Keyword(s):  
Quality Assessment ◽  
Multispectral Imaging ◽  
Seed Quality ◽  
Hyperspectral Data ◽  
Imaging Systems ◽  
Quality Monitoring ◽  
Electromagnetic Spectrum ◽  
Safety Control ◽  
Practical Applications ◽  
Wide Range

As a synergistic integration between spectroscopy and imaging technologies, spectral imaging modalities have been emerged to tackle quality evaluation dilemmas by proposing different designs with effective and practical applications in food and agriculture. With the advantage of acquiring spatio-spectral data across a wide range of the electromagnetic spectrum, the state-of-the-art multispectral imaging in tandem with different multivariate chemometric analysis scenarios has been successfully implemented not only for food quality and safety control purposes, but also in dealing with critical research challenges in seed science and technology. This paper will shed some light on the fundamental configuration of the systems and give a birds-eye view of all recent approaches in the acquisition, processing and reproduction of multispectral images for various applications in seed quality assessment and seed phenotyping issues. This review article continues from where earlier review papers stopped but it only focused on fully-operated multispectral imaging systems for quality assessment of different sorts of seeds. Thence, the review comprehensively highlights research attempts devoted to real implementations of only fully-operated multispectral imaging systems and does not consider those ones that just utilized some key wavelengths extracted from hyperspectral data analyses without building independent multispectral imaging systems. This makes this article the first attempt in briefing all published papers in multispectral imaging applications in seed phenotyping and quality monitoring by providing some examples and research results in characterizing physicochemical quality traits, predicting physiological parameters, detection of defect, pest infestation and seed health.

Hylite: a hyperspectral toolbox for open pit mapping

2020 ◽  
Author(s):  
Sam Thiele ◽  
Sandra Lorenz ◽  
Moritz Kirsch ◽  
Richard Gloaguen
Keyword(s):  
Short Wave ◽  
Mineral Deposit ◽  
Hyperspectral Data ◽  
Geological Mapping ◽  
Open Pit ◽  
Electromagnetic Spectrum ◽  
Mining Operations ◽  
Open Pit Mines ◽  
Volcanogenic Massive Sulphide ◽  
Potential Applications

&lt;p&gt;Hyperspectral imaging is a powerful tool for mapping mineralogy and lithology in core and outcrops, as many minerals show distinct spectral features in the commonly analysed visible, near, short-wave and long-wave infrared regions of the electromagnetic spectrum. High resolution ground and UAS (unmanned aerial system)-based sensors thus have significant potential as a tool for rapid and non-invasive geological mapping in mining operations, exploration campaigns and scientific research. However, the geometrical complexity of many outcrops (e.g. cliffs, open-pit mines) can result in significant technical challenges when acquiring and processing hyperspectral data. In this contribution we present updates to the previously published MEPHySTo python toolbox for correcting, georeferencing, projecting and analysing geometrically complex hyperspectral scenes. We showcase these methods using datasets covering volcanogenic massive sulphide (VMS) mineralisation exposed within open pit mines in Rio Tinto (Spain), and interpret possible structural and lithological controls on mineralization. Potential applications of hyperspectral mapping for grade control, outcrop mapping and the characterisation of different mineral deposit styles are also discussed.&lt;/p&gt;

Towards the DRED of Resin-Supported Combinatorial Libraries: A Non-Invasive Methodology Based on Bead Self-Encoding and Multispectral Imaging

2000 ◽  
Vol 112 (24) ◽  
pp. 4657-4659
Author(s):  
Hicham Fenniri ◽  
Hartmut G. Hedderich ◽  
Kenneth S. Haber ◽  
Jihane Achkar ◽  
Brian Taylor ◽  
...  
Keyword(s):  
Multispectral Imaging ◽  
Combinatorial Libraries ◽  
Non Invasive

scholarly journals MAPPING VIS AND UVL IMAGERY ON 3D GEOMETRY FOR NON-INVASIVE, NON-CONTACT ANALYSIS OF A VASE

2018 ◽  
Vol XLII-2 ◽  
pp. 773-780 ◽  
Author(s):  
E. Nocerino ◽  
D. H. Rieke-Zapp ◽  
E. Trinkl ◽  
R. Rosenbauer ◽  
E. M. Farella ◽  
...  
Keyword(s):  
3D Imaging ◽  
Multispectral Imaging ◽  
3D Models ◽  
Added Value ◽  
Non Invasive ◽  
Comprehensive Knowledge ◽  
3D Geometry ◽  
Modelling Techniques ◽  
The University

The paper presents an investigation about the combination of multispectral and 3D imaging aiming at the analysis of the condition and preservation of an ancient vase. Visible-reflected (VIS) and -induced luminescence (UVL) images are mapped to 3D models produced with image- and range-based 3D modelling techniques. The case study is an Attic vase, part of the pottery collection of the Landesmuseum Rudolfinum (Carinthia, Austria) and temporarily stored in the Institute of Archaeology of the University of Graz, Austria. The aim of this study is to exploit the added-value provided by mapping multispectral imaging onto 3D geometry for a comprehensive knowledge of the condition of a restored Cultural Heritage (CH) item.

scholarly journals Hyperspectral analysis of lithologies in the Arctic in areas with abundant lichen cover

2018 ◽  
pp. 51-55
Author(s):  
Sara Salehi
Keyword(s):  
Remote Sensing ◽  
Chemical Composition ◽  
Mineral Exploration ◽  
Spectral Characteristics ◽  
Image Data ◽  
Geological Mapping ◽  
The Arctic ◽  
Electromagnetic Spectrum ◽  
Rock Types ◽  
The Impact

Lithological mapping using remote sensing depends, in part, on the identification of rock types by their spectral characteristics. Chemical and physical properties of minerals and rocks determine their diagnostic spectral features throughout the electromagnetic spectrum. Shifts in the position and changes in the shape and depth of these features can be explained by variations in chemical composition of minerals. Detection of such variations is vital for discriminating minerals with similar chemical composition. Compared with multispectral image data, airborne or spaceborne hyperspectral imagery offers higher spectral resolution, which makes it possible to estimate the mineral composition of the rocks under study without direct contact. Arctic environments provide challenging ground for geological mapping and mineral exploration. Inaccessibility commonly complicates ground surveys, and the presence of ice, vegetation and rock-encrusting lichens hinders remote sensing surveys. This study addresses the following objectives: 1. Modelling the impact of lichen on the spectra of the rock substrate; 2. Identification of a robust lichen index for the deconvolution of lichen and rock mixtures and 3. Multiscale hyperspectral analysis of lithologies in areas with abundant lichens.

Next generation phenotyping for developing climate resilient rice varieties

2019 ◽  
Vol 56 (Special Issue) ◽  
pp. 92-105
Author(s):  
Rabi N Sahoo ◽  
C Viswanathan ◽  
Gopal Krishna ◽  
Bappa Das ◽  
Swati Goel ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Deficit ◽  
Multispectral Imaging ◽  
Sugar Content ◽  
Stress Index ◽  
Water Deficit Stress ◽  
Next Generation ◽  
Crop Water Stress Index ◽  
Non Invasive ◽  
Rice Genotypes

Present paper deals with different components of next generation phenomics for characterizing rice genotypes for water deficit stress. Major sensors used in the study were non-imaging hyperspectal remote sensing, thermal imaging at ground platform and RGB and multispectral imaging sensors from drone platform. Different spectral indices were evaluated along with new proposed index and different multivariate models were studied for non-invasive estimation of relative water content (RWC) and sugar content in rice plant using spectral reflectance data collected in spectral range 350 to 2500 nm. Spectral data were further used for spectral discrimination of rice genotypes. Crop water stress index derived from thermal images acquired for rice genotypes could well characterize the drought resistant and sensitive genotypes. Initial study on field phenotyping through drone remote sensing using multispectral and RGB sensor was also explored to capture differential response of genotypes, trait and heat map mapping. All developed protocols as reliable alternative to conventional methods are fast, economic and non-invasive and in use in plant phenomics centre for high throughput plant phenotyhping for water deficit stress studies.

Application of fluorescence spectroscopy and multispectral imaging for non-invasive estimation of GFP transfection efficiency

2014 ◽  
Author(s):  
M. Tamošiūnas ◽  
D. Jakovels ◽  
A. Ļihačovs ◽  
A. Kilikevičius ◽  
J. Baltušnikas ◽  
...  
Keyword(s):  
Fluorescence Spectroscopy ◽  
Multispectral Imaging ◽  
Transfection Efficiency ◽  
Non Invasive

scholarly journals Evaluation of Non-Invasive Multispectral Imaging as a Tool for Measuring the Effect of Systemic Therapy in Kaposi Sarcoma

PLoS ONE ◽  
2013 ◽  
Vol 8 (12) ◽  
pp. e83887 ◽  
Author(s):  
Jana M. Kainerstorfer ◽  
Mark N. Polizzotto ◽  
Thomas S. Uldrick ◽  
Rafa Rahman ◽  
Moinuddin Hassan ◽  
...  
Keyword(s):  
Systemic Therapy ◽  
Multispectral Imaging ◽  
Kaposi Sarcoma ◽  
Non Invasive
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