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Found 15 papers, 7 papers with code
A Regularized Conditional GAN for Posterior Sampling in Inverse Problems
In inverse problems, one seeks to reconstruct an image from incomplete and/or degraded measurements.
Denoising Generalized Expectation-Consistent Approximation for MR Image Recovery
To solve inverse problems, plug-and-play (PnP) methods replace the proximal step in a convex optimization algorithm with a call to an application-specific denoiser, often implemented using a deep neural network (DNN).
Technical Report (v1.0)--Pseudo-random Cartesian Sampling for Dynamic MRI
For an effective application of compressed sensing (CS), which exploits the underlying compressibility of an image, one of the requirements is that the undersampling artifact be incoherent (noise-like) in the sparsifying transform domain.
Cardiac and respiratory motion extraction for MRI using Pilot Tone-a patient study
To assess the performances of PT, ECG, and BM, cardiac and respiratory signals extracted from the RT cine images were used as the ground truth.
Maximizing Unambiguous Velocity Range in Phase-contrast MRI with Multipoint Encoding
In phase-contrast magnetic resonance imaging (PC-MRI), the velocity of spins at a voxel is encoded in the image phase.
Matching Plug-and-Play Algorithms to the Denoiser
To solve inverse problems, plug-and-play (PnP) methods have been developed that replace the proximal step in a convex optimization algorithm with a call to an application-specific denoiser, often implemented using a deep neural network (DNN).
MRI Recovery with A Self-calibrated Denoiser
The proposed method, called recovery with a self-calibrated denoiser (ReSiDe), trains the denoiser from the patches of the image being recovered.
Venc Design and Velocity Estimation for Phase Contrast MRI
We propose Phase Recovery from Multiple Wrapped Measurements (PRoM) as a fast, approximate maximum likelihood estimator of velocity from multi-coil data with possible amplitude attenuation due to dephasing.
High-dimensional Fast Convolutional Framework (HICU) for Calibrationless MRI
Purpose: To present a computational procedure for accelerated, calibrationless magnetic resonance image (Cl-MRI) reconstruction that is fast, memory efficient, and scales to high-dimensional imaging.
Fully Self-Gated Whole-Heart 4D Flow Imaging from a Five-Minute Scan
ReVEAL4D is validated using data from eight healthy volunteers and two patients and compared with a compressed sensing technique, L1-SENSE.
Automatic Extraction and Sign Determination of Respiratory Signal in Real-time Cardiac Magnetic Resonance imaging
A complete heartbeat from each slice is then used for cardiac function quantification.
Convolutional Framework for Accelerated Magnetic Resonance Imaging
Magnetic Resonance Imaging (MRI) is a noninvasive imaging technique that provides exquisite soft-tissue contrast without using ionizing radiation.
Free-breathing Cardiovascular MRI Using a Plug-and-Play Method with Learned Denoiser
We compare the reconstruction performance of PnP-DL to that of compressed sensing (CS) using eight breath-held and ten real-time (RT) free-breathing cardiac cine datasets.
Plug and play methods for magnetic resonance imaging (long version)
In this article, we describe the use of "plug-and-play" (PnP) algorithms for MRI image recovery.
Soft Computing Techniques for Dependable Cyber-Physical Systems
Cyber-Physical Systems (CPS) allow us to manipulate objects in the physical world by providing a communication bridge between computation and actuation elements.
