Dual mesh reconstruction method with depth correction for near infrared diffusive light imaging with a priori ultrasound information

2004 ◽  
Author(s):  
Minming Huang ◽  
Quing Zhu
Keyword(s):  
Near Infrared ◽  
A Priori ◽  
Reconstruction Method ◽  
Mesh Reconstruction ◽  
Dual Mesh

scholarly journals Multimodal Autoencoder Predicts fNIRS Resting State From EEG Signals

2021 ◽  
Author(s):  
Parikshat Sirpal ◽  
Rafat Damseh ◽  
Ke Peng ◽  
Dang Khoa Nguyen ◽  
Frédéric Lesage
Keyword(s):  
Near Infrared ◽  
Short Term Memory ◽  
A Priori ◽  
Functional Near Infrared Spectroscopy ◽  
Neural Data ◽  
Frequency Bands ◽  
Epileptic Patients ◽  
Brain Hemodynamics ◽  
Long Short Term Memory ◽  
Trained Neural Network

AbstractIn this work, we introduce a deep learning architecture for evaluation on multimodal electroencephalographic (EEG) and functional near-infrared spectroscopy (fNIRS) recordings from 40 epileptic patients. Long short-term memory units and convolutional neural networks are integrated within a multimodal sequence-to-sequence autoencoder. The trained neural network predicts fNIRS signals from EEG, sans a priori, by hierarchically extracting deep features from EEG full spectra and specific EEG frequency bands. Results show that higher frequency EEG ranges are predictive of fNIRS signals with the gamma band inputs dominating fNIRS prediction as compared to other frequency envelopes. Seed based functional connectivity validates similar patterns between experimental fNIRS and our model’s fNIRS reconstructions. This is the first study that shows it is possible to predict brain hemodynamics (fNIRS) from encoded neural data (EEG) in the resting human epileptic brain based on power spectrum amplitude modulation of frequency oscillations in the context of specific hypotheses about how EEG frequency bands decode fNIRS signals.

scholarly journals Validation of nine years of MOPITT V5 NIR using MOZAIC/IAGOS measurements: biases and long-term stability

2014 ◽  
Vol 7 (11) ◽  
pp. 3783-3799 ◽  
Author(s):  
A. T. J. de Laat ◽  
I. Aben ◽  
M. Deeter ◽  
P. Nédélec ◽  
H. Eskes ◽  
...  
Keyword(s):  
Near Infrared ◽  
Transport Model ◽  
A Priori ◽  
Validation Data ◽  
Chemistry Transport Model ◽  
Large Variability ◽  
Long Term Stability ◽  
Spatio Temporal ◽  
Good Agreement

Abstract. Validation results from a comparison between Measurement Of Pollution In The Troposphere (MOPITT) V5 Near InfraRed (NIR) carbon monoxide (CO) total column measurements and Measurement of Ozone and Water Vapour on Airbus in-service Aircraft (MOZAIC)/In-Service Aircraft for a Global Observing System (IAGOS) aircraft measurements are presented. A good agreement is found between MOPITT and MOZAIC/IAGOS measurements, consistent with results from earlier studies using different validation data and despite large variability in MOPITT CO total columns along the spatial footprint of the MOZAIC/IAGOS measurements. Validation results improve when taking the large spatial footprint of the MOZAIC/IAGOS data into account. No statistically significant drift was detected in the validation results over the period 2002–2010 at global, continental and local (airport) scales. Furthermore, for those situations where MOZAIC/IAGOS measurements differed from the MOPITT a priori, the MOPITT measurements clearly outperformed the MOPITT a priori data, indicating that MOPITT NIR retrievals add value to the MOPITT a priori. Results from a high spatial resolution simulation of the chemistry-transport model MOCAGE (MOdèle de Chimie Atmosphérique à Grande Echelle) showed that the most likely explanation for the large MOPITT variability along the MOZAIC-IAGOS profile flight path is related to spatio-temporal CO variability, which should be kept in mind when using MOZAIC/IAGOS profile measurements for validating satellite nadir observations.

scholarly journals Simulated retrievals for the remote sensing of CO<sub>2</sub>, CH<sub>4</sub>, CO, and H<sub>2</sub>O from geostationary orbit

2015 ◽  
Vol 8 (11) ◽  
pp. 4817-4830 ◽  
Author(s):  
X. Xi ◽  
V. Natraj ◽  
R. L. Shia ◽  
M. Luo ◽  
Q. Zhang ◽  
...  
Keyword(s):  
Near Infrared ◽  
Water Cycle ◽  
Signal To Noise Ratio ◽  
A Priori ◽  
Carbon Sources ◽  
Cost Effective ◽  
Accurate Estimation ◽  
Clear Sky ◽  
Notable Increase ◽  
Measurement Strategies

Abstract. The Geostationary Fourier Transform Spectrometer (GeoFTS) is designed to measure high-resolution spectra of reflected sunlight in three near-infrared bands centered around 0.76, 1.6, and 2.3 μm and to deliver simultaneous retrievals of column-averaged dry air mole fractions of CO2, CH4, CO, and H2O (denoted XCO2, XCH4, XCO, and XH2O, respectively) at different times of day over North America. In this study, we perform radiative transfer simulations over both clear-sky and all-sky scenes expected to be observed by GeoFTS and estimate the prospective performance of retrievals based on results from Bayesian error analysis and characterization. We find that, for simulated clear-sky retrievals, the average retrieval biases and single-measurement precisions are < 0.2 % for XCO2, XCH4, and XH2O, and < 2 % for XCO, when the a priori values have a bias of 3 % and an uncertainty of 3 %. In addition, an increase in the amount of aerosols and ice clouds leads to a notable increase in the retrieval biases and slight worsening of the retrieval precisions. Furthermore, retrieval precision is a strong function of signal-to-noise ratio and spectral resolution. This simulation study can help guide decisions on the design of the GeoFTS observing system, which can result in cost-effective measurement strategies while achieving satisfactory levels of retrieval precisions and biases. The simultaneous retrievals at different times of day will be important for more accurate estimation of carbon sources and sinks on fine spatiotemporal scales and for studies related to the atmospheric component of the water cycle.

scholarly journals A study of synthetic <sup>13</sup>CH<sub>4</sub> retrievals from TROPOMI and Sentinel-5/UVNS

2019 ◽  
Vol 12 (12) ◽  
pp. 6273-6301
Author(s):  
Edward Malina ◽  
Haili Hu ◽  
Jochen Landgraf ◽  
Ben Veihelmann
Keyword(s):  
Near Infrared ◽  
Signal To Noise Ratio ◽  
A Priori ◽  
Ultra Violet ◽  
High Signal ◽  
Atmospheric Methane ◽  
Δ13c Values ◽  
Temporal Averaging ◽  
A Minor ◽  
Shortwave Infrared

Abstract. Retrievals of methane isotopologues have the potential to differentiate between natural and anthropogenic methane sources types, which can provide much needed information about the current global methane budget. We investigate the feasibility of retrieving the second most abundant isotopologue of atmospheric methane (13CH4, roughly 1.1 % of total atmospheric methane) from the shortwave infrared (SWIR) channels of the future Sentinel-5/ultra-violet, visible, near-infrared, shortwave infrared (UVNS) and current Copernicus Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI) instruments. With the intended goal of calculating the δ13C value, we assume that a δ13C uncertainty of better than 1 ‰ is sufficient to differentiate between source types, which corresponds to a 13CH4 uncertainty of <0.02 ppb. Using the well-established information content analysis techniques and assuming clear-sky, non-scattering conditions, we find that the SWIR3 (2305–2385 nm) channel on the TROPOMI instrument can achieve a mean uncertainty of <1 ppb, while the SWIR1 channel (1590–1675 nm) on the Sentinel-5 UVNS instrument can achieve <0.68 ppb or <0.2 ppb in high signal-to-noise ratio (SNR) cases. These uncertainties combined with significant spatial and/or temporal averaging techniques can reduce δ13C uncertainty to the target magnitude or better. However, we find that 13CH4 retrievals are highly sensitive to errors in a priori knowledge of temperature and pressure, and accurate knowledge of these profiles is required before 13CH4 retrievals can be performed on TROPOMI and future Sentinel-5/UVNS data. In addition, we assess the assumption that scattering-induced light path errors are cancelled out by comparing the δ13C values calculated for non-scattering and scattering scenarios. We find that there is a minor bias in δ13C values from scattering and non-scattering retrievals, but this is unrelated to scattering-induced errors.

scholarly journals Quantitative assessment of near-infrared spectroscopy time course under hypercapnia using an a priori model-based fitting

2020 ◽  
Vol 118 ◽  
pp. 103638
Author(s):  
Victor Vagné ◽  
Emmanuelle Le Bars ◽  
Jérémy Deverdun ◽  
Olivier Rossel ◽  
Stéphane Perrey ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Quantitative Assessment ◽  
Time Course ◽  
Near Infrared ◽  
A Priori ◽  
Model Based

scholarly journals 7.3. Sgr A∗ in the mid-infrared reference frame: no evidence of an infrared counterpart, or interaction with nearby sources

1998 ◽  
Vol 184 ◽  
pp. 295-297
Author(s):  
Dan Gezari
Keyword(s):  
Near Infrared ◽  
Reference Frames ◽  
A Priori ◽  
Infrared Emission ◽  
Mid Infrared ◽  
Source Component ◽  
Comparable Accuracy ◽  
Sgr A ◽  
Central Parsec ◽  
Infrared Sources

We have determined the position of Sgr A∗ with respect to the mid-infrared (5-25 m) sources in the central parsec by direct correlation of our 12.4 m array image (Gezari et al. 1994) and the new 2-cm continuum VLA map (Yusef-Zadeh 1997; private communication), without a priori knowledge of any other position determinations. Menten et al. (1997) recently succeeded in registering the radio and near-infrared (2.2 m) reference frames with high precision (+0.03 arcsec) using VLA observations of Sgr A∗, SiO masers and H2O masers. Unfortunately, registering the mid-infrared and radio reference frames with comparable accuracy cannot be done by applying the 2.2 m calibration. Most near-infrared sources have no detectable mid-infrared counterparts, and it is not obvious which of those that do are coincident (if any), since near-infrared and mid-infrared emission generally does not arise from the same physical source component. Dramatic examples of shifts between the brightest near- and mid-infrared peaks can be seen in Orion BN/KL and the Ney-Allen Nebula (Gezari and Backman 1994; Gezari, Backman and Werner 1997) corresponding to 0.1 - 0.5 arcsec if they were located at 8.5 kpc. Further, several Sgr A West IRS sources are displaced significantly in the infrared and radio, suggesting they may actually be compact clusters of objects.

scholarly journals Method for Quantitative Broadband Diffuse Optical Spectroscopy of Tumor-Like Inclusions

2020 ◽  
Vol 10 (4) ◽  
pp. 1419 ◽  
Author(s):  
Sandhya Vasudevan ◽  
Farnoush Forghani ◽  
Chris Campbell ◽  
Savannah Bedford ◽  
Thomas D. O’Sullivan
Keyword(s):  
Optical Properties ◽  
Optical Absorption ◽  
Near Infrared ◽  
Continuous Wave ◽  
A Priori ◽  
Hybrid Technique ◽  
Scattering Spectra ◽  
Heterogeneous Tissue ◽  
The Mean ◽  
Homogeneous Background

A hybrid reflectance-based diffuse optical imaging (DOI) technique combining discrete wavelength frequency-domain (FD) near-infrared spectroscopy (NIRS) with broadband continuous wave NIRS measurements was developed to quantify the broadband optical properties of deep tumor-like inclusions. This method was developed to more accurately measure the broadband optical properties of human tumors using a compact handheld imaging probe and without requiring a priori spectral constraints. We simulated the reconstruction of absorption and scattering spectra (650–1000 nm) of human breast tumors in a homogeneous background at depths of 0 to 10 mm. The hybrid DOI technique demonstrated enhanced performance in reconstruction of optical absorption with a mean accuracy over all 71 wavelengths of 8.39% versus 32.26% for a 10 mm deep tumor with the topographic DOI method. The new hybrid technique was also tested and validated on two heterogeneous tissue-simulating phantoms with inclusion depths of 2, 7, and 9 mm. The mean optical absorption accuracy over all wavelengths was similarly improved up to 5x for the hybrid DOI method versus topographic DOI for the deepest inclusions.

scholarly journals A method for improved SCIAMACHY CO2 retrieval in the presence of optically thin clouds

2010 ◽  
Vol 3 (1) ◽  
pp. 209-232 ◽  
Author(s):  
M. Reuter ◽  
M. Buchwitz ◽  
O. Schneising ◽  
J. Heymann ◽  
H. Bovensmann ◽  
...  
Keyword(s):  
Absorption Band ◽  
Near Infrared ◽  
A Priori ◽  
Optimal Estimation ◽  
Surface Flux ◽  
Co2 Absorption ◽  
Retrieval Scheme ◽  
Priori Information ◽  
Transfer Of Information

Abstract. An optimal estimation based retrieval scheme for satellite based retrievals of XCO2 (the dry air column averaged mixing ratio of atmospheric CO2) is presented enabling accurate retrievals also in the presence of thin clouds. The proposed method is designed to analyze near-infrared nadir measurements of the SCIAMACHY instrument in the CO2 absorption band at 1580 nm and in the O2-A absorption band at around 760 nm. The algorithm accounts for scattering in an optically thin cirrus cloud layer and at aerosols of a default profile. The scattering information is mainly obtained from the O2-A band and a merged fit windows approach enables the transfer of information between the O2-A and the CO2 band. Via the optimal estimation technique, the algorithm is able to account for a priori information to further constrain the inversion. Test scenarios of simulated SCIAMACHY sun-normalized radiance measurements are analyzed in order to specify the quality of the proposed method. In contrast to existing algorithms for SCIAMACHY retrievals, the systematic errors due to cirrus clouds with optical thicknesses up to 1.0 are reduced to values below 4 ppm for most of the analyzed scenarios. This shows that the proposed method has the potential to reduce uncertainties of SCIAMACHY retrieved XCO2 making this data product potentially useful for surface flux inverse modeling.

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