Mehmet Akçakaya

According to our database1, Mehmet Akçakaya authored at least 47 papers between 2007 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2020
Tensor Completion From Regular Sub-Nyquist Samples.
IEEE Trans. Signal Process., 2020

Low-Rank Tensor Models for Improved Multidimensional MRI: Application to Dynamic Cardiac T<sub>1</sub> Mapping.
IEEE Trans. Computational Imaging, 2020

Deep-Learning Methods for Parallel Magnetic Resonance Imaging Reconstruction: A Survey of the Current Approaches, Trends, and Issues.
IEEE Signal Process. Mag., 2020

A field-monitoring-based approach for correcting eddy-current-induced artifacts of up to the 2<sup>nd</sup> spatial order in human-connectome-project-style multiband diffusion MRI experiment at 7T: A pilot study.
NeuroImage, 2020

Dense Recurrent Neural Networks for Accelerated MRI: History-Cognizant Unrolling of Optimization Algorithms.
IEEE J. Sel. Top. Signal Process., 2020

Self-Supervised Physics-Guided Deep Learning Reconstruction For High-Resolution 3D LGE CMR.
CoRR, 2020

Improved Supervised Training of Physics-Guided Deep Learning Image Reconstruction with Multi-Masking.
CoRR, 2020

Multi-Mask Self-Supervised Learning for Physics-Guided Neural Networks in Highly Accelerated MRI.
CoRR, 2020

Noise2Inpaint: Learning Referenceless Denoising by Inpainting Unrolling.
CoRR, 2020

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset.
CoRR, 2020

Automated Acquisition Planning for Magnetic Resonance Spectroscopy in Brain Cancer.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Self-Supervised Physics-Based Deep Learning MRI Reconstruction Without Fully-Sampled Data.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Scan-Specific Accelerated Mri Reconstruction Using Recurrent Neural Networks In A Regularized Self-Consistent Framework.
Proceedings of the 2020 IEEE 17th International Symposium on Biomedical Imaging Workshops (ISBI Workshops), 2020

Improved Simultaneous Multi-Slice Imaging for Perfusion Cardiac MRI Using Outer Volume Suppression and Regularized Reconstruction.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

High-Fidelity Accelerated MRI Reconstruction by Scan-Specific Fine-Tuning of Physics-Based Neural Networks.
Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

2019
Self-Supervised Learning of Physics-Based Reconstruction Neural Networks without Fully-Sampled Reference Data.
CoRR, 2019

Dense Recurrent Neural Networks for Inverse Problems: History-Cognizant Unrolling of Optimization Algorithms.
CoRR, 2019

Deep Learning Methods for Parallel Magnetic Resonance Image Reconstruction.
CoRR, 2019

Robust Online Spike Recovery for High-Density Electrode Recordings using Convolutional Compressed Sensing.
Proceedings of the 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), 2019

Accelerated Coronary Mri Using 3D Spirit-Raki With Sparsity Regularization.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Regular Sampling of Tensor Signals: Theory and Application to FMRI.
Proceedings of the IEEE International Conference on Acoustics, 2019

Improved Regularized Reconstruction for Simultaneous Multi-Slice Cardiac MRI T1 Mapping.
Proceedings of the 27th European Signal Processing Conference, 2019

Functional LGE Imaging: Cardiac Phase-Resolved Assessment of Focal Fibrosis.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

Scan-Specific Residual Convolutional Neural Networks for Fast MRI Using Residual RAKI.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018
Sparse Phase Retrieval via Truncated Amplitude Flow.
IEEE Trans. Signal Process., 2018

Electromagnetic Brain Source Imaging by Means of a Robust Minimum Variance Beamformer.
IEEE Trans. Biomed. Eng., 2018

Subject-Specific Convolutional Neural Networks for Accelerated Magnetic Resonance Imaging.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Fully Automatic Segmentation of the Right Ventricle Via Multi-Task Deep Neural Networks.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Fast GPU Implementation of a Scan-Specific Deep Learning Reconstruction for Accelerated Magnetic Resonance Imaging.
Proceedings of the 2018 IEEE International Conference on Electro/Information Technology, 2018

Accelerated Simultaneous Multi-Slice MRI using Subject-Specific Convolutional Neural Networks.
Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

2017
SPARTA: Sparse phase retrieval via Truncated Amplitude flow.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Multi-scale locally low-rank noise reduction for high-resolution dynamic quantitative cardiac MRI.
Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017

Locally Low-Rank tensor regularization for high-resolution quantitative dynamic MRI.
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

2015
Sparse Signal Recovery from a Mixture of Linear and Magnitude-Only Measurements.
IEEE Signal Process. Lett., 2015

2013
New Conditions for Sparse Phase Retrieval.
CoRR, 2013

Distortion-based achievability conditions for joint estimation of sparse signals and measurement parameters from undersampled acquisitions.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

2011
A Coding Theory Approach to Noisy Compressive Sensing Using Low Density Frames.
IEEE Trans. Signal Process., 2011

Compressed Sensing With Wavelet Domain Dependencies for Coronary MRI: A Retrospective Study.
IEEE Trans. Medical Imaging, 2011

2010
Shannon-theoretic limits on noisy compressive sampling.
IEEE Trans. Inf. Theory, 2010

Low density frames for compressive sensing.
Proceedings of the IEEE International Conference on Acoustics, 2010

2009
Compressive Sensing Using Low Density Frames
CoRR, 2009

2008
A Frame Construction and a Universal Distortion Bound for Sparse Representations.
IEEE Trans. Signal Process., 2008

Noisy compressive sampling limits in linear and sublinear regimes.
Proceedings of the 42nd Annual Conference on Information Sciences and Systems, 2008

2007
Performance of Sparse Representation Algorithms Using Randomly Generated Frames.
IEEE Signal Process. Lett., 2007

Performance Bounds on Sparse Representations Using Redundant Frames
CoRR, 2007

On Sparsity, Redundancy and Quality of Frame Representations.
Proceedings of the IEEE International Symposium on Information Theory, 2007

Performance Study of Various Sparse Representation Methods Using Redundant Frames.
Proceedings of the 41st Annual Conference on Information Sciences and Systems, 2007


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