Search Results for author: Rizwan Ahmad

Found 15 papers, 7 papers with code

A Regularized Conditional GAN for Posterior Sampling in Inverse Problems

1 code implementation24 Oct 2022 Matthew Bendel, Rizwan Ahmad, Philip Schniter

In inverse problems, one seeks to reconstruct an image from incomplete and/or degraded measurements.

Deblurring Super-Resolution

Denoising Generalized Expectation-Consistent Approximation for MR Image Recovery

2 code implementations9 Jun 2022 Saurav K. Shastri, Rizwan Ahmad, Christopher A. Metzler, Philip Schniter

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

1 code implementation8 Jun 2022 Mihir Joshi, Aaron Pruitt, Chong Chen, Yingmin Liu, Rizwan Ahmad

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

no code implementations31 Jan 2022 Chong Chen, Yingmin Liu, Orlando P. Simonetti, Matthew Tong, Ning Jin, Mario Bacher, Peter Speier, Rizwan Ahmad

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

no code implementations7 Nov 2021 Shen Zhao, Rizwan Ahmad, Lee C. Potter

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

no code implementations NeurIPS Workshop Deep_Invers 2021 Saurav K Shastri, Rizwan Ahmad, Christopher Metzler, Philip Schniter

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

no code implementations18 Oct 2021 Sizhuo Liu, Philip Schniter, Rizwan Ahmad

The proposed method, called recovery with a self-calibrated denoiser (ReSiDe), trains the denoiser from the patches of the image being recovered.

Denoising MRI Reconstruction

Venc Design and Velocity Estimation for Phase Contrast MRI

1 code implementation26 Sep 2021 Shen Zhao, Rizwan Ahmad, Lee C. Potter

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

1 code implementation19 Apr 2020 Shen Zhao, Lee C. Potter, Rizwan Ahmad

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.

MRI Reconstruction

Fully Self-Gated Whole-Heart 4D Flow Imaging from a Five-Minute Scan

no code implementations19 Apr 2020 Aaron Pruitt, Adam Rich, Yingmin Liu, Ning Jin, Lee Potter, Matthew Tong, Saurabh Rajpal, Orlando Simonetti, Rizwan Ahmad

ReVEAL4D is validated using data from eight healthy volunteers and two patients and compared with a compressed sensing technique, L1-SENSE.

Convolutional Framework for Accelerated Magnetic Resonance Imaging

1 code implementation8 Feb 2020 Shen Zhao, Lee C. Potter, Kiryung Lee, Rizwan Ahmad

Magnetic Resonance Imaging (MRI) is a noninvasive imaging technique that provides exquisite soft-tissue contrast without using ionizing radiation.

Image Reconstruction

Free-breathing Cardiovascular MRI Using a Plug-and-Play Method with Learned Denoiser

no code implementations8 Feb 2020 Sizhuo Liu, Edward Reehorst, Philip Schniter, Rizwan Ahmad

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.


Soft Computing Techniques for Dependable Cyber-Physical Systems

no code implementations25 Jan 2018 Muhammad Atif, Siddique Latif, Rizwan Ahmad, Adnan Khalid Kiani, Junaid Qadir, Adeel Baig, Hisao Ishibuchi, Waseem Abbas

Cyber-Physical Systems (CPS) allow us to manipulate objects in the physical world by providing a communication bridge between computation and actuation elements.

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