Sorry, you need to enable JavaScript to visit this website.

Biomedical signal processing

Characterizing unobserved factors driving local field potential dynamics underlying a time-varying spike generation


Neural spiking responses are generated by both extrinsic covariates such as sensory variables and intrinsic covariates such as those rep-resenting the state of a system. Although the external covariates can be directly controlled or measured; the internal factors are hard, if not impossible, to control or even observe. This study provides a statistical framework that enables characterization of the unobserved factors controlling neuronal response variability induced by behavior, with the model parameters fitted directly to real spiking data.

Paper Details

Authors:
Kaiser Niknam, Amir Akbarian, Behrad Noudoost, Neda Nategh
Submitted On:
26 November 2018 - 11:32pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Niknam

(6)

Subscribe

[1] Kaiser Niknam, Amir Akbarian, Behrad Noudoost, Neda Nategh, "Characterizing unobserved factors driving local field potential dynamics underlying a time-varying spike generation", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3803. Accessed: Apr. 22, 2019.
@article{3803-18,
url = {http://sigport.org/3803},
author = {Kaiser Niknam; Amir Akbarian; Behrad Noudoost; Neda Nategh },
publisher = {IEEE SigPort},
title = {Characterizing unobserved factors driving local field potential dynamics underlying a time-varying spike generation},
year = {2018} }
TY - EJOUR
T1 - Characterizing unobserved factors driving local field potential dynamics underlying a time-varying spike generation
AU - Kaiser Niknam; Amir Akbarian; Behrad Noudoost; Neda Nategh
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3803
ER -
Kaiser Niknam, Amir Akbarian, Behrad Noudoost, Neda Nategh. (2018). Characterizing unobserved factors driving local field potential dynamics underlying a time-varying spike generation. IEEE SigPort. http://sigport.org/3803
Kaiser Niknam, Amir Akbarian, Behrad Noudoost, Neda Nategh, 2018. Characterizing unobserved factors driving local field potential dynamics underlying a time-varying spike generation. Available at: http://sigport.org/3803.
Kaiser Niknam, Amir Akbarian, Behrad Noudoost, Neda Nategh. (2018). "Characterizing unobserved factors driving local field potential dynamics underlying a time-varying spike generation." Web.
1. Kaiser Niknam, Amir Akbarian, Behrad Noudoost, Neda Nategh. Characterizing unobserved factors driving local field potential dynamics underlying a time-varying spike generation [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3803

StationPlot: A New Non-stationarity Quantification Tool for Detection of Epileptic Seizures


A novel non-stationarity visualization tool known as StationPlot is developed for deciphering the chaotic behavior of a dynamical time series. A family of analytic measures enumerating geometrical aspects of the non-stationarity & degree of variability is formulated by convex hull geometry (CHG) on StationPlot. In the Euclidean space, both trend-stationary (TS) & difference-stationary (DS) perturbations are comprehended by the asymmetric structure of StationPlot's region of interest (ROI).

Paper Details

Authors:
Sawon Pratiher, Subhankar Chattoraj, Rajdeep Mukherjee
Submitted On:
26 November 2018 - 2:05pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Oral_StationPlot_GlobalSIP_2018

(5)

Subscribe

[1] Sawon Pratiher, Subhankar Chattoraj, Rajdeep Mukherjee, "StationPlot: A New Non-stationarity Quantification Tool for Detection of Epileptic Seizures", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3778. Accessed: Apr. 22, 2019.
@article{3778-18,
url = {http://sigport.org/3778},
author = {Sawon Pratiher; Subhankar Chattoraj; Rajdeep Mukherjee },
publisher = {IEEE SigPort},
title = {StationPlot: A New Non-stationarity Quantification Tool for Detection of Epileptic Seizures},
year = {2018} }
TY - EJOUR
T1 - StationPlot: A New Non-stationarity Quantification Tool for Detection of Epileptic Seizures
AU - Sawon Pratiher; Subhankar Chattoraj; Rajdeep Mukherjee
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3778
ER -
Sawon Pratiher, Subhankar Chattoraj, Rajdeep Mukherjee. (2018). StationPlot: A New Non-stationarity Quantification Tool for Detection of Epileptic Seizures. IEEE SigPort. http://sigport.org/3778
Sawon Pratiher, Subhankar Chattoraj, Rajdeep Mukherjee, 2018. StationPlot: A New Non-stationarity Quantification Tool for Detection of Epileptic Seizures. Available at: http://sigport.org/3778.
Sawon Pratiher, Subhankar Chattoraj, Rajdeep Mukherjee. (2018). "StationPlot: A New Non-stationarity Quantification Tool for Detection of Epileptic Seizures." Web.
1. Sawon Pratiher, Subhankar Chattoraj, Rajdeep Mukherjee. StationPlot: A New Non-stationarity Quantification Tool for Detection of Epileptic Seizures [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3778

POLARITY INVARIANT TRANSFORMATION FOR EEG MICROSTATES ANALYSIS


Electroencephalography (EEG) has been widely used in human brain research. Several techniques in EEG relies on analyzing the topographical distribution of the data. One of the most common analysis is EEG microstate (EEG-ms). EEG-ms reflects the stable topographical representation of EEG signal lasting a few dozen milliseconds. EEG-ms were associated with resting state fMRI networks and were associated with mental processes and abnormalities.

Paper Details

Authors:
Ahmad Mayeli, Hazem Refai, Martin Paulus, Jerzy Bodurka
Submitted On:
23 November 2018 - 8:20pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

A presentation for polarity invariant transformation for EEG microstates analysis

(4)

Subscribe

[1] Ahmad Mayeli, Hazem Refai, Martin Paulus, Jerzy Bodurka , "POLARITY INVARIANT TRANSFORMATION FOR EEG MICROSTATES ANALYSIS", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3761. Accessed: Apr. 22, 2019.
@article{3761-18,
url = {http://sigport.org/3761},
author = {Ahmad Mayeli; Hazem Refai; Martin Paulus; Jerzy Bodurka },
publisher = {IEEE SigPort},
title = {POLARITY INVARIANT TRANSFORMATION FOR EEG MICROSTATES ANALYSIS},
year = {2018} }
TY - EJOUR
T1 - POLARITY INVARIANT TRANSFORMATION FOR EEG MICROSTATES ANALYSIS
AU - Ahmad Mayeli; Hazem Refai; Martin Paulus; Jerzy Bodurka
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3761
ER -
Ahmad Mayeli, Hazem Refai, Martin Paulus, Jerzy Bodurka . (2018). POLARITY INVARIANT TRANSFORMATION FOR EEG MICROSTATES ANALYSIS. IEEE SigPort. http://sigport.org/3761
Ahmad Mayeli, Hazem Refai, Martin Paulus, Jerzy Bodurka , 2018. POLARITY INVARIANT TRANSFORMATION FOR EEG MICROSTATES ANALYSIS. Available at: http://sigport.org/3761.
Ahmad Mayeli, Hazem Refai, Martin Paulus, Jerzy Bodurka . (2018). "POLARITY INVARIANT TRANSFORMATION FOR EEG MICROSTATES ANALYSIS." Web.
1. Ahmad Mayeli, Hazem Refai, Martin Paulus, Jerzy Bodurka . POLARITY INVARIANT TRANSFORMATION FOR EEG MICROSTATES ANALYSIS [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3761

Contact Surface Area: A Novel Signal for Heart Rate Estimation in Smartphone Videos


Smartphone video-based measurement of heart rate typically uses photoplethysmography (PPG). Prior accuracy studies report low mean absolute errors for apps based on contact PPG on a fingertip, but substantial errors on a troubling percentage of measurements. In this study, we aimed to reduce the rate of substantial heart rate estimation errors by introducing a novel signal present in fingertip videos: fingertip contact surface area.

Paper Details

Authors:
Sara Fridovich-Keil, Peter J. Ramadge
Submitted On:
27 November 2018 - 1:59am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

GlobalSIP2018_archived_v4.pdf

(35)

Subscribe

[1] Sara Fridovich-Keil, Peter J. Ramadge, "Contact Surface Area: A Novel Signal for Heart Rate Estimation in Smartphone Videos", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3753. Accessed: Apr. 22, 2019.
@article{3753-18,
url = {http://sigport.org/3753},
author = {Sara Fridovich-Keil; Peter J. Ramadge },
publisher = {IEEE SigPort},
title = {Contact Surface Area: A Novel Signal for Heart Rate Estimation in Smartphone Videos},
year = {2018} }
TY - EJOUR
T1 - Contact Surface Area: A Novel Signal for Heart Rate Estimation in Smartphone Videos
AU - Sara Fridovich-Keil; Peter J. Ramadge
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3753
ER -
Sara Fridovich-Keil, Peter J. Ramadge. (2018). Contact Surface Area: A Novel Signal for Heart Rate Estimation in Smartphone Videos. IEEE SigPort. http://sigport.org/3753
Sara Fridovich-Keil, Peter J. Ramadge, 2018. Contact Surface Area: A Novel Signal for Heart Rate Estimation in Smartphone Videos. Available at: http://sigport.org/3753.
Sara Fridovich-Keil, Peter J. Ramadge. (2018). "Contact Surface Area: A Novel Signal for Heart Rate Estimation in Smartphone Videos." Web.
1. Sara Fridovich-Keil, Peter J. Ramadge. Contact Surface Area: A Novel Signal for Heart Rate Estimation in Smartphone Videos [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3753

ADAPTIVE CSP FOR USER INDEPENDENCE IN MI-BCI PARADIGM FOR UPPER LIMB STROKE REHABILITATION

Paper Details

Authors:
Ana P. Costa, Jakob S. Møller, Helle K. Iversen, Sadasivan Puthusserypady
Submitted On:
22 November 2018 - 7:05pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Costa_et_al_2018_presentation.pdf

(41)

Subscribe

[1] Ana P. Costa, Jakob S. Møller, Helle K. Iversen, Sadasivan Puthusserypady, "ADAPTIVE CSP FOR USER INDEPENDENCE IN MI-BCI PARADIGM FOR UPPER LIMB STROKE REHABILITATION", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3723. Accessed: Apr. 22, 2019.
@article{3723-18,
url = {http://sigport.org/3723},
author = {Ana P. Costa; Jakob S. Møller; Helle K. Iversen; Sadasivan Puthusserypady },
publisher = {IEEE SigPort},
title = {ADAPTIVE CSP FOR USER INDEPENDENCE IN MI-BCI PARADIGM FOR UPPER LIMB STROKE REHABILITATION},
year = {2018} }
TY - EJOUR
T1 - ADAPTIVE CSP FOR USER INDEPENDENCE IN MI-BCI PARADIGM FOR UPPER LIMB STROKE REHABILITATION
AU - Ana P. Costa; Jakob S. Møller; Helle K. Iversen; Sadasivan Puthusserypady
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3723
ER -
Ana P. Costa, Jakob S. Møller, Helle K. Iversen, Sadasivan Puthusserypady. (2018). ADAPTIVE CSP FOR USER INDEPENDENCE IN MI-BCI PARADIGM FOR UPPER LIMB STROKE REHABILITATION. IEEE SigPort. http://sigport.org/3723
Ana P. Costa, Jakob S. Møller, Helle K. Iversen, Sadasivan Puthusserypady, 2018. ADAPTIVE CSP FOR USER INDEPENDENCE IN MI-BCI PARADIGM FOR UPPER LIMB STROKE REHABILITATION. Available at: http://sigport.org/3723.
Ana P. Costa, Jakob S. Møller, Helle K. Iversen, Sadasivan Puthusserypady. (2018). "ADAPTIVE CSP FOR USER INDEPENDENCE IN MI-BCI PARADIGM FOR UPPER LIMB STROKE REHABILITATION." Web.
1. Ana P. Costa, Jakob S. Møller, Helle K. Iversen, Sadasivan Puthusserypady. ADAPTIVE CSP FOR USER INDEPENDENCE IN MI-BCI PARADIGM FOR UPPER LIMB STROKE REHABILITATION [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3723

ELECTROPHYSIOLOGICAL SIGNAL PROCESSING FOR INTRAOPERATIVE LOCALIZATION OF SUBTHALAMIC NUCLEUS DURING DEEP BRAIN STIMULATION SURGERY

Paper Details

Authors:
Submitted On:
26 November 2018 - 7:02pm
Short Link:
Type:
Event:

Document Files

globalsip.pdf

(31)

Subscribe

[1] , "ELECTROPHYSIOLOGICAL SIGNAL PROCESSING FOR INTRAOPERATIVE LOCALIZATION OF SUBTHALAMIC NUCLEUS DURING DEEP BRAIN STIMULATION SURGERY", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3722. Accessed: Apr. 22, 2019.
@article{3722-18,
url = {http://sigport.org/3722},
author = { },
publisher = {IEEE SigPort},
title = {ELECTROPHYSIOLOGICAL SIGNAL PROCESSING FOR INTRAOPERATIVE LOCALIZATION OF SUBTHALAMIC NUCLEUS DURING DEEP BRAIN STIMULATION SURGERY},
year = {2018} }
TY - EJOUR
T1 - ELECTROPHYSIOLOGICAL SIGNAL PROCESSING FOR INTRAOPERATIVE LOCALIZATION OF SUBTHALAMIC NUCLEUS DURING DEEP BRAIN STIMULATION SURGERY
AU -
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3722
ER -
. (2018). ELECTROPHYSIOLOGICAL SIGNAL PROCESSING FOR INTRAOPERATIVE LOCALIZATION OF SUBTHALAMIC NUCLEUS DURING DEEP BRAIN STIMULATION SURGERY. IEEE SigPort. http://sigport.org/3722
, 2018. ELECTROPHYSIOLOGICAL SIGNAL PROCESSING FOR INTRAOPERATIVE LOCALIZATION OF SUBTHALAMIC NUCLEUS DURING DEEP BRAIN STIMULATION SURGERY. Available at: http://sigport.org/3722.
. (2018). "ELECTROPHYSIOLOGICAL SIGNAL PROCESSING FOR INTRAOPERATIVE LOCALIZATION OF SUBTHALAMIC NUCLEUS DURING DEEP BRAIN STIMULATION SURGERY." Web.
1. . ELECTROPHYSIOLOGICAL SIGNAL PROCESSING FOR INTRAOPERATIVE LOCALIZATION OF SUBTHALAMIC NUCLEUS DURING DEEP BRAIN STIMULATION SURGERY [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3722

OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS


Speech production involves the synchronization of neural activity between the speech centers of the brain and the oralmotor system, allowing for the conversion of thoughts into

Paper Details

Authors:
Debadatta Dash, Paul Ferrari, Saleem Malik, Jun Wang
Submitted On:
22 November 2018 - 2:18pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Dash_oral_GlobalSIP_MEG.pdf

(48)

Subscribe

[1] Debadatta Dash, Paul Ferrari, Saleem Malik, Jun Wang, "OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3719. Accessed: Apr. 22, 2019.
@article{3719-18,
url = {http://sigport.org/3719},
author = {Debadatta Dash; Paul Ferrari; Saleem Malik; Jun Wang },
publisher = {IEEE SigPort},
title = {OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS},
year = {2018} }
TY - EJOUR
T1 - OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS
AU - Debadatta Dash; Paul Ferrari; Saleem Malik; Jun Wang
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3719
ER -
Debadatta Dash, Paul Ferrari, Saleem Malik, Jun Wang. (2018). OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS. IEEE SigPort. http://sigport.org/3719
Debadatta Dash, Paul Ferrari, Saleem Malik, Jun Wang, 2018. OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS. Available at: http://sigport.org/3719.
Debadatta Dash, Paul Ferrari, Saleem Malik, Jun Wang. (2018). "OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS." Web.
1. Debadatta Dash, Paul Ferrari, Saleem Malik, Jun Wang. OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3719

Low-Complexity Compressed Analysis in Eigenspace with Limited Labeled Data for Real-Time Electrocardiography Telemonitoring


To achieve real-time electrocardiography (ECG) telemonitoring, we need to overcome the scarce bandwidth. Compressed sensing (CS) emerges as a promising technique to greatly compress ECG signal with little computation. Furthermore, with edge-classification, we can reduce the data rate by transmitting abnormal ECG signals only. However, there are three main limitations: limited number of labeled ECG signal, tight battery constraint of edge devices and low response time requirement.

Paper Details

Authors:
Kai-Chieh Hsu, Bo-Hong Cho, Ching-Yao Chou, and An-Yeu (Andy) Wu
Submitted On:
12 December 2018 - 10:09pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

GlobalSIP_slides.pdf

(36)

Subscribe

[1] Kai-Chieh Hsu, Bo-Hong Cho, Ching-Yao Chou, and An-Yeu (Andy) Wu, "Low-Complexity Compressed Analysis in Eigenspace with Limited Labeled Data for Real-Time Electrocardiography Telemonitoring", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3718. Accessed: Apr. 22, 2019.
@article{3718-18,
url = {http://sigport.org/3718},
author = {Kai-Chieh Hsu; Bo-Hong Cho; Ching-Yao Chou; and An-Yeu (Andy) Wu },
publisher = {IEEE SigPort},
title = {Low-Complexity Compressed Analysis in Eigenspace with Limited Labeled Data for Real-Time Electrocardiography Telemonitoring},
year = {2018} }
TY - EJOUR
T1 - Low-Complexity Compressed Analysis in Eigenspace with Limited Labeled Data for Real-Time Electrocardiography Telemonitoring
AU - Kai-Chieh Hsu; Bo-Hong Cho; Ching-Yao Chou; and An-Yeu (Andy) Wu
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3718
ER -
Kai-Chieh Hsu, Bo-Hong Cho, Ching-Yao Chou, and An-Yeu (Andy) Wu. (2018). Low-Complexity Compressed Analysis in Eigenspace with Limited Labeled Data for Real-Time Electrocardiography Telemonitoring. IEEE SigPort. http://sigport.org/3718
Kai-Chieh Hsu, Bo-Hong Cho, Ching-Yao Chou, and An-Yeu (Andy) Wu, 2018. Low-Complexity Compressed Analysis in Eigenspace with Limited Labeled Data for Real-Time Electrocardiography Telemonitoring. Available at: http://sigport.org/3718.
Kai-Chieh Hsu, Bo-Hong Cho, Ching-Yao Chou, and An-Yeu (Andy) Wu. (2018). "Low-Complexity Compressed Analysis in Eigenspace with Limited Labeled Data for Real-Time Electrocardiography Telemonitoring." Web.
1. Kai-Chieh Hsu, Bo-Hong Cho, Ching-Yao Chou, and An-Yeu (Andy) Wu. Low-Complexity Compressed Analysis in Eigenspace with Limited Labeled Data for Real-Time Electrocardiography Telemonitoring [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3718

A PROJECTION CCA METHOD FOR EFFECTIVE FMRI DATA ANALYSIS


Canonical correlation analysis (CCA) is a data-driven method that has been successfully used in functional magnetic resonance imaging (fMRI) data analysis. Standard CCA extracts meaningful information from a data set by seeking pairs of linear combinations from two sets of variables with maximum pairwise correlation. So far, however, this method has been used without incorporating prior information available for fMRI data. In this paper, we address this issue by proposing a new CCA method named PCCA (for projection CCA).

Paper Details

Authors:
Muhammad Ali Qadar and Abd-Krim Seghouane
Submitted On:
6 October 2018 - 1:34pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Final_2018_ICIP_Poster_PCCA.pdf

(68)

Subscribe

[1] Muhammad Ali Qadar and Abd-Krim Seghouane, "A PROJECTION CCA METHOD FOR EFFECTIVE FMRI DATA ANALYSIS", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3487. Accessed: Apr. 22, 2019.
@article{3487-18,
url = {http://sigport.org/3487},
author = {Muhammad Ali Qadar and Abd-Krim Seghouane },
publisher = {IEEE SigPort},
title = {A PROJECTION CCA METHOD FOR EFFECTIVE FMRI DATA ANALYSIS},
year = {2018} }
TY - EJOUR
T1 - A PROJECTION CCA METHOD FOR EFFECTIVE FMRI DATA ANALYSIS
AU - Muhammad Ali Qadar and Abd-Krim Seghouane
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3487
ER -
Muhammad Ali Qadar and Abd-Krim Seghouane. (2018). A PROJECTION CCA METHOD FOR EFFECTIVE FMRI DATA ANALYSIS. IEEE SigPort. http://sigport.org/3487
Muhammad Ali Qadar and Abd-Krim Seghouane, 2018. A PROJECTION CCA METHOD FOR EFFECTIVE FMRI DATA ANALYSIS. Available at: http://sigport.org/3487.
Muhammad Ali Qadar and Abd-Krim Seghouane. (2018). "A PROJECTION CCA METHOD FOR EFFECTIVE FMRI DATA ANALYSIS." Web.
1. Muhammad Ali Qadar and Abd-Krim Seghouane. A PROJECTION CCA METHOD FOR EFFECTIVE FMRI DATA ANALYSIS [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3487

Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy


Fourier Transform Interferometry (FTI) is an interferometric procedure for acquiring HyperSpectral (HS) data. Recently, it has been observed that the light source highlighting a (biologic) sample can be coded before the FTI acquisition in a procedure called Coded Illumination-FTI (CI-FTI). This turns HS data reconstruction into a Compressive Sensing (CS) problem regularized by the sparsity of the HS data. CI-FTI combines the high spectral resolution of FTI with the advantages of reduced-light-exposure imaging in biology.

Paper Details

Authors:
Amirafshar Moshtaghpour, Laurent Jacques
Submitted On:
4 October 2018 - 9:29am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Compressive Fourier Transform Interferometry

(63)

Subscribe

[1] Amirafshar Moshtaghpour, Laurent Jacques, "Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3405. Accessed: Apr. 22, 2019.
@article{3405-18,
url = {http://sigport.org/3405},
author = {Amirafshar Moshtaghpour; Laurent Jacques },
publisher = {IEEE SigPort},
title = {Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy},
year = {2018} }
TY - EJOUR
T1 - Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy
AU - Amirafshar Moshtaghpour; Laurent Jacques
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3405
ER -
Amirafshar Moshtaghpour, Laurent Jacques. (2018). Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy. IEEE SigPort. http://sigport.org/3405
Amirafshar Moshtaghpour, Laurent Jacques, 2018. Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy. Available at: http://sigport.org/3405.
Amirafshar Moshtaghpour, Laurent Jacques. (2018). "Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy." Web.
1. Amirafshar Moshtaghpour, Laurent Jacques. Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3405

Pages