1 code implementation • 24 Oct 2022 • Matthew Bendel, Rizwan Ahmad, Philip Schniter
In inverse problems, one seeks to reconstruct an image from incomplete and/or degraded measurements.
2 code implementations • 9 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).
1 code implementation • 8 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.
no code implementations • 31 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.
no code implementations • 7 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.
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).
no code implementations • 18 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.
1 code implementation • 26 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.
1 code implementation • 19 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.
no code implementations • 19 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.
1 code implementation • 8 Feb 2020 • Chong Chen, Yingmin Liu, Orlando P. Simonetti, Rizwan Ahmad
A complete heartbeat from each slice is then used for cardiac function quantification.
1 code implementation • 8 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.
no code implementations • 8 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.
no code implementations • 20 Mar 2019 • Rizwan Ahmad, Charles A. Bouman, Gregery T. Buzzard, Stanley Chan, Sizhou Liu, Edward T. Reehorst, Philip Schniter
In this article, we describe the use of "plug-and-play" (PnP) algorithms for MRI image recovery.
no code implementations • 25 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.