Near-infrared diffuse tomography combined with a priori MRI structural information: testing a hybrid image reconstruction methodology with functional imaging of the rat cranium

1999 ◽  
Author(s):  
Brian W. Pogue ◽  
Troy O. McBride ◽  
Casmiar Nwaigwe ◽  
Ulf L. Oesterberg ◽  
Jeffrey F. Dunn ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Functional Imaging ◽  
Near Infrared ◽  
Structural Information ◽  
A Priori

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.

MR-GUIDED PULSE OXIMETRY IMAGING OF BREAST IN VIVO

2011 ◽  
Vol 04 (02) ◽  
pp. 199-208
Author(s):  
ZHIQIU LI ◽  
SHUDONG JIANG ◽  
VENKATARAMANAN KRISHNASWAMY ◽  
SCOTT C. DAVIS ◽  
SUBHADRA SRINIVASAN ◽  
...  
Keyword(s):  
Breast Tissue ◽  
Near Infrared ◽  
Imaging System ◽  
Structural Information ◽  
Human Subjects ◽  
Nir Spectroscopy ◽  
Tomography System ◽  
Finger Pulse ◽  
Lock In

A near-infrared (NIR) tomography system with spectrally-encoded sources in two wavelength bands was built to quantify the temporal oxyhemoglobin and deoxyhemoglobin contrast in breast tissue at a 20 Hz bandwidth. The system was integrated into a 3 T magnetic resonance (MR) imaging system through a customized breast coil interface for simultaneous optical and MRI acquisition. In this configuration, the MR images provide breast tissue structural information for NIR spectroscopy of adipose and fibro-glandular tissue in breast. Spectral characterization performance of the NIR system was verified through dynamic phantom experiments. Normal human subjects were imaged with finger pulse oximeter (PO) plethysmogram synchronized to the NIR system to provide a frequency-locked reference. Both the raw data from the NIR system and the recovered absorption coefficients of the breast at two wavelengths showed the same frequency of about 1.3 Hz as the PO output. The frequency lock-in approach provided a practical platform for MR-localized recovery of small pulsatile variations of oxyhemoglobin and deoxyhemoglobin in the breast, which are related to the heartbeat and vascular resistance of the tissue.

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.

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