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

Medical imaging

LINE DETECTION IN SPECKLE IMAGES USING RADON TRANSFORM AND L1 REGULARIZATION

Paper Details

Authors:
Submitted On:
5 March 2017 - 12:42pm
Short Link:
Type:
Event:
Document Year:
Cite

Document Files

linerestoration.pptx

(53 downloads)

Keywords

Subscribe

[1] , " LINE DETECTION IN SPECKLE IMAGES USING RADON TRANSFORM AND L1 REGULARIZATION", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1633. Accessed: Aug. 19, 2017.
@article{1633-17,
url = {http://sigport.org/1633},
author = { },
publisher = {IEEE SigPort},
title = { LINE DETECTION IN SPECKLE IMAGES USING RADON TRANSFORM AND L1 REGULARIZATION},
year = {2017} }
TY - EJOUR
T1 - LINE DETECTION IN SPECKLE IMAGES USING RADON TRANSFORM AND L1 REGULARIZATION
AU -
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1633
ER -
. (2017). LINE DETECTION IN SPECKLE IMAGES USING RADON TRANSFORM AND L1 REGULARIZATION. IEEE SigPort. http://sigport.org/1633
, 2017. LINE DETECTION IN SPECKLE IMAGES USING RADON TRANSFORM AND L1 REGULARIZATION. Available at: http://sigport.org/1633.
. (2017). " LINE DETECTION IN SPECKLE IMAGES USING RADON TRANSFORM AND L1 REGULARIZATION." Web.
1. . LINE DETECTION IN SPECKLE IMAGES USING RADON TRANSFORM AND L1 REGULARIZATION [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1633

Sparse Reconstruction for Fluorescence Lifetime Imaging Microscopy with Poisson Noise


We present a novel, three-stage method to solve the fluorescence lifetime imaging problem under low-photon conditions. In particular, we reconstruct the fluorophore concentration along with its support and fluorescence lifetime from the time-dependent measurements of scattered light exiting the domain. Because detectors used for these problems are photon counting devices, measurements are corrupted by Poisson noise. Consequently, we explicitly consider Poisson noise in conjunction with SPIRAL-$\ell_p$ -- a sparsity-promoting nonconvex optimization method -- to solve this problem.

Paper Details

Authors:
Lasith Adhikari, Arnold D. Kim, Roummel F. Marcia
Submitted On:
7 December 2016 - 10:28am
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

FLIM with Poisson

(869 downloads)

Keywords

Additional Categories

Subscribe

[1] Lasith Adhikari, Arnold D. Kim, Roummel F. Marcia, "Sparse Reconstruction for Fluorescence Lifetime Imaging Microscopy with Poisson Noise", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/1406. Accessed: Aug. 19, 2017.
@article{1406-16,
url = {http://sigport.org/1406},
author = {Lasith Adhikari; Arnold D. Kim; Roummel F. Marcia },
publisher = {IEEE SigPort},
title = {Sparse Reconstruction for Fluorescence Lifetime Imaging Microscopy with Poisson Noise},
year = {2016} }
TY - EJOUR
T1 - Sparse Reconstruction for Fluorescence Lifetime Imaging Microscopy with Poisson Noise
AU - Lasith Adhikari; Arnold D. Kim; Roummel F. Marcia
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/1406
ER -
Lasith Adhikari, Arnold D. Kim, Roummel F. Marcia. (2016). Sparse Reconstruction for Fluorescence Lifetime Imaging Microscopy with Poisson Noise. IEEE SigPort. http://sigport.org/1406
Lasith Adhikari, Arnold D. Kim, Roummel F. Marcia, 2016. Sparse Reconstruction for Fluorescence Lifetime Imaging Microscopy with Poisson Noise. Available at: http://sigport.org/1406.
Lasith Adhikari, Arnold D. Kim, Roummel F. Marcia. (2016). "Sparse Reconstruction for Fluorescence Lifetime Imaging Microscopy with Poisson Noise." Web.
1. Lasith Adhikari, Arnold D. Kim, Roummel F. Marcia. Sparse Reconstruction for Fluorescence Lifetime Imaging Microscopy with Poisson Noise [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/1406

Fast Dynamic MRI using Linear Dynamical System Model

Paper Details

Authors:
Vimal Singh, Ahmed Tewfik
Submitted On:
20 March 2016 - 3:51pm
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ICASSP2016_draft3.pptx

(172 downloads)

ICASSP2016_draft2.pptx

(150 downloads)

Keywords

Subscribe

[1] Vimal Singh, Ahmed Tewfik, "Fast Dynamic MRI using Linear Dynamical System Model", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/759. Accessed: Aug. 19, 2017.
@article{759-16,
url = {http://sigport.org/759},
author = {Vimal Singh; Ahmed Tewfik },
publisher = {IEEE SigPort},
title = {Fast Dynamic MRI using Linear Dynamical System Model},
year = {2016} }
TY - EJOUR
T1 - Fast Dynamic MRI using Linear Dynamical System Model
AU - Vimal Singh; Ahmed Tewfik
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/759
ER -
Vimal Singh, Ahmed Tewfik. (2016). Fast Dynamic MRI using Linear Dynamical System Model. IEEE SigPort. http://sigport.org/759
Vimal Singh, Ahmed Tewfik, 2016. Fast Dynamic MRI using Linear Dynamical System Model. Available at: http://sigport.org/759.
Vimal Singh, Ahmed Tewfik. (2016). "Fast Dynamic MRI using Linear Dynamical System Model." Web.
1. Vimal Singh, Ahmed Tewfik. Fast Dynamic MRI using Linear Dynamical System Model [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/759

Super-resolution spectral analysis for ultrasound scatter characterization


Parametric Bayesian spectral estimation methods have been previously utilized to improve frequency resolution. Ultrasound signals have been tested in such methods resulting in higher precision frequency detection compared to common non-parametric spectral estimation methods based on the Fourier transform. Such a technique using a reversible jump Markov Chain Monte Carlo algorithm has been developed to fully characterize signals and in addition to frequency, to provide amplitude and noise estimation.

poster.pdf

PDF icon poster.pdf (263 downloads)

Paper Details

Authors:
Maruf A. Dhali, Gavin Gibson, Yan Yan, James R. Hopgood, Vassilis Sboros
Submitted On:
11 March 2016 - 7:28pm
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

poster.pdf

(263 downloads)

Keywords

Subscribe

[1] Maruf A. Dhali, Gavin Gibson, Yan Yan, James R. Hopgood, Vassilis Sboros, "Super-resolution spectral analysis for ultrasound scatter characterization", IEEE SigPort, 2016. [Online]. Available: http://sigport.org/615. Accessed: Aug. 19, 2017.
@article{615-16,
url = {http://sigport.org/615},
author = {Maruf A. Dhali; Gavin Gibson; Yan Yan; James R. Hopgood; Vassilis Sboros },
publisher = {IEEE SigPort},
title = {Super-resolution spectral analysis for ultrasound scatter characterization},
year = {2016} }
TY - EJOUR
T1 - Super-resolution spectral analysis for ultrasound scatter characterization
AU - Maruf A. Dhali; Gavin Gibson; Yan Yan; James R. Hopgood; Vassilis Sboros
PY - 2016
PB - IEEE SigPort
UR - http://sigport.org/615
ER -
Maruf A. Dhali, Gavin Gibson, Yan Yan, James R. Hopgood, Vassilis Sboros. (2016). Super-resolution spectral analysis for ultrasound scatter characterization. IEEE SigPort. http://sigport.org/615
Maruf A. Dhali, Gavin Gibson, Yan Yan, James R. Hopgood, Vassilis Sboros, 2016. Super-resolution spectral analysis for ultrasound scatter characterization. Available at: http://sigport.org/615.
Maruf A. Dhali, Gavin Gibson, Yan Yan, James R. Hopgood, Vassilis Sboros. (2016). "Super-resolution spectral analysis for ultrasound scatter characterization." Web.
1. Maruf A. Dhali, Gavin Gibson, Yan Yan, James R. Hopgood, Vassilis Sboros. Super-resolution spectral analysis for ultrasound scatter characterization [Internet]. IEEE SigPort; 2016. Available from : http://sigport.org/615

Magnetic Resonance and computed Tomography Image Fusion using Bidimensional Empirical Mode Decomposition

Paper Details

Authors:
Fathi E. Abd El-Samie
Submitted On:
23 February 2016 - 1:38pm
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

BEMD fusion slides.pdf

(229 downloads)

Keywords

Subscribe

[1] Fathi E. Abd El-Samie, "Magnetic Resonance and computed Tomography Image Fusion using Bidimensional Empirical Mode Decomposition", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/497. Accessed: Aug. 19, 2017.
@article{497-15,
url = {http://sigport.org/497},
author = {Fathi E. Abd El-Samie },
publisher = {IEEE SigPort},
title = {Magnetic Resonance and computed Tomography Image Fusion using Bidimensional Empirical Mode Decomposition},
year = {2015} }
TY - EJOUR
T1 - Magnetic Resonance and computed Tomography Image Fusion using Bidimensional Empirical Mode Decomposition
AU - Fathi E. Abd El-Samie
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/497
ER -
Fathi E. Abd El-Samie. (2015). Magnetic Resonance and computed Tomography Image Fusion using Bidimensional Empirical Mode Decomposition. IEEE SigPort. http://sigport.org/497
Fathi E. Abd El-Samie, 2015. Magnetic Resonance and computed Tomography Image Fusion using Bidimensional Empirical Mode Decomposition. Available at: http://sigport.org/497.
Fathi E. Abd El-Samie. (2015). "Magnetic Resonance and computed Tomography Image Fusion using Bidimensional Empirical Mode Decomposition." Web.
1. Fathi E. Abd El-Samie. Magnetic Resonance and computed Tomography Image Fusion using Bidimensional Empirical Mode Decomposition [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/497

Magnetic Resonance and computed Tomography Image Fusion using Bidimensional Empirical Mode Decomposition

Paper Details

Authors:
Fathi E. Abd El-Samie
Submitted On:
23 February 2016 - 1:44pm
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

BEMD fusion slides.pdf

(212 downloads)

Keywords

Subscribe

[1] Fathi E. Abd El-Samie, "Magnetic Resonance and computed Tomography Image Fusion using Bidimensional Empirical Mode Decomposition", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/418. Accessed: Aug. 19, 2017.
@article{418-15,
url = {http://sigport.org/418},
author = {Fathi E. Abd El-Samie },
publisher = {IEEE SigPort},
title = {Magnetic Resonance and computed Tomography Image Fusion using Bidimensional Empirical Mode Decomposition},
year = {2015} }
TY - EJOUR
T1 - Magnetic Resonance and computed Tomography Image Fusion using Bidimensional Empirical Mode Decomposition
AU - Fathi E. Abd El-Samie
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/418
ER -
Fathi E. Abd El-Samie. (2015). Magnetic Resonance and computed Tomography Image Fusion using Bidimensional Empirical Mode Decomposition. IEEE SigPort. http://sigport.org/418
Fathi E. Abd El-Samie, 2015. Magnetic Resonance and computed Tomography Image Fusion using Bidimensional Empirical Mode Decomposition. Available at: http://sigport.org/418.
Fathi E. Abd El-Samie. (2015). "Magnetic Resonance and computed Tomography Image Fusion using Bidimensional Empirical Mode Decomposition." Web.
1. Fathi E. Abd El-Samie. Magnetic Resonance and computed Tomography Image Fusion using Bidimensional Empirical Mode Decomposition [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/418

A novel nonlocal MRI reconstruction algorithm with patch-based low rank regularization


This is the presentation slides on the IEEE GlobalSIP2015 paper:"A novel nonlocal MRI reconstruction algorithm with patch-based low rank regularization".

For more information, you can refer to the paper and discuss with us on the conference.

Paper Details

Authors:
Jinchu Chen, Delu Zeng, Xinghao Ding
Submitted On:
23 February 2016 - 1:44pm
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

Presentation.pdf

(680 downloads)

Keywords

Subscribe

[1] Jinchu Chen, Delu Zeng, Xinghao Ding, "A novel nonlocal MRI reconstruction algorithm with patch-based low rank regularization", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/372. Accessed: Aug. 19, 2017.
@article{372-15,
url = {http://sigport.org/372},
author = {Jinchu Chen; Delu Zeng; Xinghao Ding },
publisher = {IEEE SigPort},
title = {A novel nonlocal MRI reconstruction algorithm with patch-based low rank regularization},
year = {2015} }
TY - EJOUR
T1 - A novel nonlocal MRI reconstruction algorithm with patch-based low rank regularization
AU - Jinchu Chen; Delu Zeng; Xinghao Ding
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/372
ER -
Jinchu Chen, Delu Zeng, Xinghao Ding. (2015). A novel nonlocal MRI reconstruction algorithm with patch-based low rank regularization. IEEE SigPort. http://sigport.org/372
Jinchu Chen, Delu Zeng, Xinghao Ding, 2015. A novel nonlocal MRI reconstruction algorithm with patch-based low rank regularization. Available at: http://sigport.org/372.
Jinchu Chen, Delu Zeng, Xinghao Ding. (2015). "A novel nonlocal MRI reconstruction algorithm with patch-based low rank regularization." Web.
1. Jinchu Chen, Delu Zeng, Xinghao Ding. A novel nonlocal MRI reconstruction algorithm with patch-based low rank regularization [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/372

Joint Estimation of Activity Signal and HRF in fMRI using Fused LASSO

Paper Details

Authors:
Priya Aggarwal, Ajay Garg
Submitted On:
23 February 2016 - 1:44pm
Short Link:
Type:
Event:
Presenter's Name:
Document Year:
Cite

Document Files

Anubha_GlobalSip_Dec5_2015_fMRI.pptx

(240 downloads)

Anubha_GlobalSip_Dec5_2015_fMRI.pdf

(181 downloads)

Keywords

Subscribe

[1] Priya Aggarwal, Ajay Garg, "Joint Estimation of Activity Signal and HRF in fMRI using Fused LASSO", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/265. Accessed: Aug. 19, 2017.
@article{265-15,
url = {http://sigport.org/265},
author = {Priya Aggarwal; Ajay Garg },
publisher = {IEEE SigPort},
title = {Joint Estimation of Activity Signal and HRF in fMRI using Fused LASSO},
year = {2015} }
TY - EJOUR
T1 - Joint Estimation of Activity Signal and HRF in fMRI using Fused LASSO
AU - Priya Aggarwal; Ajay Garg
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/265
ER -
Priya Aggarwal, Ajay Garg. (2015). Joint Estimation of Activity Signal and HRF in fMRI using Fused LASSO. IEEE SigPort. http://sigport.org/265
Priya Aggarwal, Ajay Garg, 2015. Joint Estimation of Activity Signal and HRF in fMRI using Fused LASSO. Available at: http://sigport.org/265.
Priya Aggarwal, Ajay Garg. (2015). "Joint Estimation of Activity Signal and HRF in fMRI using Fused LASSO." Web.
1. Priya Aggarwal, Ajay Garg. Joint Estimation of Activity Signal and HRF in fMRI using Fused LASSO [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/265

A fast weighted stochastic gradient descent algorithm for image reconstruction in 3D computed tomography


Abstract—We describe and evaluate an algorithm for image reconstruction in 3D x-ray computed tomography. The proposed algorithm is similar to the class of projected gradient methods. The gradient descent for reducing the measurement misfit term is carried out using a stochastic gradient iteration and the gradient directions are weighted using weights suggested by parallel coordinate descent.

Paper Details

Authors:
Submitted On:
23 February 2016 - 1:44pm
Short Link:
Type:

Document Files

PCD Reconstruction.pdf

(394 downloads)

Keywords

Subscribe

[1] , "A fast weighted stochastic gradient descent algorithm for image reconstruction in 3D computed tomography", IEEE SigPort, 2015. [Online]. Available: http://sigport.org/178. Accessed: Aug. 19, 2017.
@article{178-15,
url = {http://sigport.org/178},
author = { },
publisher = {IEEE SigPort},
title = {A fast weighted stochastic gradient descent algorithm for image reconstruction in 3D computed tomography},
year = {2015} }
TY - EJOUR
T1 - A fast weighted stochastic gradient descent algorithm for image reconstruction in 3D computed tomography
AU -
PY - 2015
PB - IEEE SigPort
UR - http://sigport.org/178
ER -
. (2015). A fast weighted stochastic gradient descent algorithm for image reconstruction in 3D computed tomography. IEEE SigPort. http://sigport.org/178
, 2015. A fast weighted stochastic gradient descent algorithm for image reconstruction in 3D computed tomography. Available at: http://sigport.org/178.
. (2015). "A fast weighted stochastic gradient descent algorithm for image reconstruction in 3D computed tomography." Web.
1. . A fast weighted stochastic gradient descent algorithm for image reconstruction in 3D computed tomography [Internet]. IEEE SigPort; 2015. Available from : http://sigport.org/178