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An Approach for Characterizing and Comparing Hyperspectral Microscopy Systems
2013
Sensors
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Hyperspectral imaging and analysis approaches offer accurate detection and quantification of fluorescently-labeled proteins and cells in highly autofluorescent tissues. ...
These studies provide a framework for optimization that can be applied to a variety of hyperspectral imaging systems. ...
Acknowledgements The authors would like to acknowledge support from NIH grant awards P01HL066299 and S10RR027535, and would like to thank Nikon Instruments for providing the Hsi-300 tunable filter. ...
doi:10.3390/s130709267
pmid:23877125
pmcid:PMC3758648
fatcat:5yco7sfe7zhizcmhmds22r7jre
Hyperspectral imaging microscopy for identification and quantitative analysis of fluorescently-labeled cells in highly autofluorescent tissue
2011
Journal of Biophotonics
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Here we describe the use of hyperspectral analysis techniques to resolve and quantify fluorescently labeled cells in highly autofluorescent lung tissue. ...
These results demonstrate that hyperspectral analysis approaches uniquely offer accurate and precise detection and quantification of fluorescence signals in highly autofluorescent tissues. Medicine. ...
The authors would also like to acknowledge support from the International Society for the Advancement of Cytometry Scholar's Program and to thank Nikon Instruments for providing the HSi-300 tunable filter ...
doi:10.1002/jbio.201100066
pmid:21987373
pmcid:PMC3517021
fatcat:varkhhihd5cczhphhf54adploy
Assessing FRET using spectral techniques
2013
Cytometry Part A
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In this study, we have compared traditional (filter-based) FRET approaches to three spectral-based approaches: the ratio of acceptor-to-donor peak emission, linear spectral unmixing, and linear spectral ...
Using spectral approaches, single-cell measurements were conducted through hyperspectral confocal microscopy, linear unmixing, and cell segmentation with quantitative image analysis. ...
Conti for providing plasmids encoding CFP, YFP, and CFP-Epac-YFP, and to acknowledge support from NIH grants P01 HL066299, R01 HL094455, and S10 RR027535, NSF grant DBI-1156596, the University of South ...
doi:10.1002/cyto.a.22340
pmid:23929684
pmcid:PMC4374658
fatcat:odcx7k4rszg73orvvsvwl3t7im
Excitation-scanning hyperspectral imaging microscope
2014
Journal of Biomedical Optics
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However, these emission-scanning approaches have shown reduced sensitivity due to light attenuation from spectral filtering. ...
These results demonstrate excitation scanning has utility in a wide range of time-dependent and photosensitive applications. ...
VersaChrome filters and tuning hardware for this study were provided by Semrock Inc., a Unit of IDEX. ...
doi:10.1117/1.jbo.19.4.046010
pmid:24727909
pmcid:PMC3983524
fatcat:o2cgjer7l5ewbiwts5mymcursq
Optical hyperspectral imaging in microscopy and spectroscopy - a review of data acquisition
2014
Journal of Biophotonics
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Rather than simply acting as a photographic camera capturing two-dimensional (x, y) intensity images or a spectrometer acquiring spectra (λ), a hyperspectral imager measures entire threedimensional (x, ...
Such data also gives clinical insights for disease diagnosis and treatment. ...
Ballard for close reading of the manuscript. This work was sponsored by the National Institutes of Health (NIH) under grants EY015520 and EY021470. ...
doi:10.1002/jbio.201400051
pmid:25186815
pmcid:PMC4348353
fatcat:emox7mu7nrhjjfbqzdwk5rk7iu
SULoRA: Subspace Unmixing With Low-Rank Attribute Embedding for Hyperspectral Data Analysis
2018
IEEE Journal on Selected Topics in Signal Processing
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To support high-level analysis of spaceborne imaging spectroscopy (hyperspectral) imagery, spectral unmixing has been gaining significance in recent years. ...
Index Terms-Alternating direction method of multipliers, hyperspectral data analysis, low-rank attribute embedding, remote sensing, subspace unmixing, spectral variability. ...
Bioucas-Dias for providing MATLAB codes with respect to PLMM and SUnSAL tested in their experiments, and the Hyperspectral Digital Imagery Collection Experiment for sharing the urban dataset free of charge ...
doi:10.1109/jstsp.2018.2877497
fatcat:7ihr5yaulvc5dh7pwtz7fw7juy
Thin-film tunable filters for hyperspectral fluorescence microscopy
2013
Journal of Biomedical Optics
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Hyperspectral imaging is a powerful tool that acquires data from many spectral bands, forming a contiguous spectrum. ...
The spectral filtering method largely determines the sensitivity and specificity of any hyperspectral imaging system. ...
., a Unit of IDEX. ...
doi:10.1117/1.jbo.19.1.011017
pmid:24077519
pmcid:PMC3784641
fatcat:kt6qdyjjqvdudihiocix25kmum
Advances in Hyperspectral Image and Signal Processing: A Comprehensive Overview of the State of the Art
2017
IEEE Geoscience and Remote Sensing Magazine
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This paper offers a comprehensive tutorial/overview focusing specifically on hyperspectral data analysis, which is categorized into seven broad topics: classification, spectral unmixing, dimensionality ...
Recent advances in airborne and spaceborne hyperspectral imaging technology have provided end users with rich spectral, spatial, and temporal information, which make a plethora of applications for the ...
In addition, the authors would like to thank the National Center for Airborne Laser Mapping (NCALM) at the University of Houston for providing the CASI Houston data set, and the IEEE GRSS Image Analysis ...
doi:10.1109/mgrs.2017.2762087
fatcat:6ezzye7yyvacbouduqv2f2c7gi
Hyperspectral image quality for unmixing and subpixel detection applications
2013
Image Quality and System Performance X
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The quality of remotely sensed hyperspectral images is not easily assessed visually, as the value of the imagery is primarily inherent in the spectral information embedded in the data. ...
Our approach is a combination of empirical analyses of airborne hyperspectral imagery together with system modeling driven by real input data. ...
ACKNOWLEDGMENTS The authors would like to acknowledge the efforts of several colleagues in fabricating, deploying, and measuring ground truth for the targets used in the experiment: Bo Ding, Kim Horan, ...
doi:10.1117/12.2001693
fatcat:am4urcxnq5fmjlkbyhq7v6hg3i
MUSIC-CSR: Hyperspectral Unmixing via Multiple Signal Classification and Collaborative Sparse Regression
2014
IEEE Transactions on Geoscience and Remote Sensing
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Sparse unmixing has attracted much attention as it sidesteps two common limitations of classic spectral unmixing approaches, namely, the lack of pure pixels in hyperspectral scenes and the need to estimate ...
Spectral unmixing aims at finding the spectrally pure constituent materials (also called endmembers) and their respective fractional abundances in each pixel of a hyperspectral image scene. ...
DC1, DC2, AND DC3 the analysis, thus obtaining a data set with 1798 spectral bands. ...
doi:10.1109/tgrs.2013.2281589
fatcat:7llbkr5vijh23btguqz2qhxoym
Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches
2012
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Due to low spatial resolution of HSCs, microscopic material mixing, and multiple scattering, spectra measured by HSCs are mixtures of spectra of materials in a scene. ...
Thus, accurate estimation requires unmixing. Pixels are assumed to be mixtures of a few materials, called endmembers. ...
Green and the AVIRIS team for making the Rcuprite hyperspectral data set available to the community, and the United States Geological Survey (USGS) for their publicly available library of mineral signatures ...
doi:10.1109/jstars.2012.2194696
fatcat:s66a35xjd5dqzkw5wwihq6ux64
Spectral Characterization and Unmixing of Intrinsic Contrast in Intact Normal and Diseased Gastric Tissues Using Hyperspectral Two-Photon Microscopy
2011
PLoS ONE
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Using these four excitation signatures as basis spectra, linear unmixing strategies were applied to hyperspectral data sets of both normal and neoplastic tissue acquired in the colon and small intestine ...
We obtained hyperspectral data at subcellular resolution by acquiring images over a range of two-photon excitation wavelengths, and found excitation spectral signatures of specific tissue types based on ...
Analyzed the data: LEG EMCH. Contributed reagents/materials/analysis tools: AJR SA TCW. Wrote the paper: LEG EMCH. ...
doi:10.1371/journal.pone.0019925
pmid:21603623
pmcid:PMC3095627
fatcat:ly7ycrmeafgoneljvzr544q5ha
Hyperspectral Local Intrinsic Dimensionality
2016
IEEE Transactions on Geoscience and Remote Sensing
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The Intrinsic Dimensionality (ID) of multivariate data is a very important concept in spectral unmixing of hyperspectral images. ...
Recently, some approaches to perform spectral unmixing and super-resolution locally have been proposed, which require a local estimation of the number of endmembers to use. ...
The CASI 1500 image used in this paper has been acquired in the framework of the SEN2FLEX campaign and is provided by ESA under the project 6519. ...
doi:10.1109/tgrs.2016.2536480
fatcat:qz66drlrhja7lf7c2xktkihcyu
Spectral Variability in Hyperspectral Data Unmixing: A Comprehensive Review
[article]
2021
arXiv
pre-print
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This resulted in the development of algorithms that incorporate different strategies to allow the EMs to vary within a hyperspectral image, using, for instance, sets of spectral signatures known a priori ...
Traditional spectral unmixing (SU) algorithms neglect the spectral variability of the endmembers, what propagates significant mismodeling errors throughout the whole unmixing process and compromises the ...
of up to 0.11, and a strong sensitivity to moisture/optical depth (visibility) errors [22] . ...
arXiv:2001.07307v3
fatcat:6ambb6x2pzgoxott3jqt3hts2i
Spectral-Spatial Constrained Nonnegative Matrix Factorization for Spectral Mixture Analysis of Hyperspectral images
2021
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Specifically, a spatial neighborhood preserving constraint is proposed to preserve the local geometric structure of the hyperspectral data by assuming that pixels in a spatial neighborhood generally fall ...
Hyperspectral spectral mixture analysis (SMA), which intends to decompose mixed pixels into a collection of endmembers weighted by their corresponding fraction abundances, has been successfully used to ...
Recently, abundance constrained NMF algorithms have gained great attention in SMA of hyperspectral images. ...
doi:10.1109/jstars.2021.3092566
fatcat:b5br6f6q45a2pcrq3xqvxgjam4
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