Built-in hyperspectral camera for smartphone in visible, near-infrared and middle-infrared lights region (second report): sensitivity improvement of Fourier-spectroscopic imaging to detect diffuse reflection lights from internal human tissues for healthcare sensors

2016 ◽  
Author(s):  
Natsumi Kawashima ◽  
Satsuki Hosono ◽  
Ichiro Ishimaru
Keyword(s):  
Near Infrared ◽  
Diffuse Reflection ◽  
Spectroscopic Imaging ◽  
Human Tissues ◽  
Sensitivity Improvement ◽  
Middle Infrared ◽  
Hyperspectral Camera

Quantitative Determination of Pharmaceutical Drug Formulations by Near-Infrared Spectroscopic Imaging

2008 ◽  
Vol 62 (11) ◽  
pp. 1200-1208 ◽  
Author(s):  
O. Kolomiets ◽  
U. Hoffmann ◽  
P. Geladi ◽  
H. W. Siesler
Keyword(s):  
Quantitative Determination ◽  
Focal Plane ◽  
Near Infrared ◽  
Diffuse Reflection ◽  
Spectroscopic Imaging ◽  
Focal Plane Array ◽  
Drug Formulation ◽  
Array Detector ◽  
Ft Ir

Over the last decade Fourier transform infrared (FT-IR) and near-infrared (NIR) spectroscopic imaging with focal plane array (FPA) detectors have proved powerful techniques for the rapid visualization of samples by a combination of spectroscopic and spatial information. Using these methods, selected sample areas can be analyzed with reference to the identification and localization of chemical species by FT-IR spectroscopy in the transmission or attenuated total reflection (ATR) mode and by NIR spectroscopy in diffuse reflection with a lateral resolution in the micrometer range. The present communication focuses on the quantitative determination of the active ingredient composition of a solid drug formulation by NIR spectroscopic imaging with a focal plane array detector and the results obtained are compared to the quantitative data obtained by conservative light-fiber NIR spectroscopic diffuse reflection measurements with a single-element detector. The communication also addresses the issue of penetration depth of NIR radiation into the investigated solid material.

scholarly journals Rapid Quantification of Microalgae Growth with Hyperspectral Camera and Vegetation Indices

Plants ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 341
Author(s):  
Pauliina Salmi ◽  
Matti A. Eskelinen ◽  
Matti T. Leppänen ◽  
Ilkka Pölönen
Keyword(s):  
Chlorophyll Fluorescence ◽  
Chlorophyll A ◽  
Near Infrared ◽  
Vegetation Indices ◽  
Hyperspectral Data ◽  
Strong Correlations ◽  
Algae Biomass ◽  
Chlorophyll A Concentration ◽  
Cost Efficient ◽  
Hyperspectral Camera

Spectral cameras are traditionally used in remote sensing of microalgae, but increasingly also in laboratory-scale applications, to study and monitor algae biomass in cultures. Practical and cost-efficient protocols for collecting and analyzing hyperspectral data are currently needed. The purpose of this study was to test a commercial, easy-to-use hyperspectral camera to monitor the growth of different algae strains in liquid samples. Indices calculated from wavebands from transmission imaging were compared against algae abundance and wet biomass obtained from an electronic cell counter, chlorophyll a concentration, and chlorophyll fluorescence. A ratio of selected wavebands containing near-infrared and red turned out to be a powerful index because it was simple to calculate and interpret, yet it yielded strong correlations to abundances strain-specifically (0.85 < r < 0.96, p < 0.001). When all the indices formulated as A/B, A/(A + B) or (A − B)/(A + B), where A and B were wavebands of the spectral camera, were scrutinized, good correlations were found amongst them for biomass of each strain (0.66 < r < 0.98, p < 0.001). Comparison of near-infrared/red index to chlorophyll a concentration demonstrated that small-celled strains had higher chlorophyll absorbance compared to strains with larger cells. The comparison of spectral imaging to chlorophyll fluorescence was done for one strain of green algae and yielded strong correlations (near-infrared/red, r = 0.97, p < 0.001). Consequently, we described a simple imaging setup and information extraction based on vegetation indices that could be used to monitor algae cultures.

scholarly journals Analysis of Variance in Spectroscopic Imaging Data from Human Tissues

2011 ◽  
Vol 84 (2) ◽  
pp. 1063-1069 ◽  
Author(s):  
Jin Tae Kwak ◽  
Rohith Reddy ◽  
Saurabh Sinha ◽  
Rohit Bhargava
Keyword(s):  
Analysis Of Variance ◽  
Spectroscopic Imaging ◽  
Human Tissues ◽  
Imaging Data

Reflectance characteristics of cumulative defoliation of balsam fir

1988 ◽  
Vol 18 (8) ◽  
pp. 1008-1016 ◽  
Author(s):  
D. G. Leckie ◽  
P. M. Teillet ◽  
G. Fedosejevs ◽  
D. P. Ostaff
Keyword(s):  
Near Infrared ◽  
Spectral Characteristics ◽  
Broad Band ◽  
Integrating Sphere ◽  
Simple Relationship ◽  
Spectral Bands ◽  
Infrared Wavelengths ◽  
Remote Sensing Techniques ◽  
Middle Infrared ◽  
Airborne Sensors

Knowledge of the spectral characteristics of trees with varying degrees of needle loss is essential for developing remote sensing techniques for assessing defoliation. Spectra covering the range 400–2400 nm were acquired for single tree crowns suffering varying degrees of cumulative defoliation due to the spruce budworm (Choristoneurafumiferana (Clem.)), using a spectrometer mounted in the bucket of a boom truck. Spectra over the range 360–1100 nm were also obtained for the components of defoliated trees (i.e., needles, bare branches, and lichen), using a separate spectrometer and integrating sphere. Estimates of defoliation symptoms of each tree were made from the ground and above the tree. Changes in reflectance had a close and simple relationship with the defoliation symptoms measured. The spectral differences due to cumulative defoliation that were observed were broad-band features. The best spectral regions for differentiating levels of cumulative defoliation symptoms were the blue, red, shorter near-infrared wavelengths, and middle-infrared. Although currently available satellite and airborne sensors operate in these spectral regions, defoliation assessment may be improved by the use of optimized spectral bands.

A time-gated near-infrared spectroscopic imaging device for clinical applications.

2013 ◽  
Author(s):  
Patrick Poulet ◽  
Wilfried Uhring ◽  
Walter Hanselmann ◽  
René Glazenborg ◽  
Farouk Nouizi ◽  
...  
Keyword(s):  
Near Infrared ◽  
Spectroscopic Imaging ◽  
Clinical Applications ◽  
Imaging Device ◽  
Infrared Spectroscopic ◽  
Infrared Spectroscopic Imaging
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