Mathews Jacob
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Explore the profile of Mathews Jacob including associated specialties, affiliations and a list of published articles.
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Articles
129
Citations
1368
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Recent Articles
11.
Pramanik A, Bhave S, Sajib S, Sharma S, Jacob M
Magn Reson Med
. 2023 Jun;
90(5):2033-2051.
PMID: 37332189
Purpose: The aim of this work is to introduce a single model-based deep network that can provide high-quality reconstructions from undersampled parallel MRI data acquired with multiple sequences, acquisition settings,...
12.
Pramanik A, Zimmerman M, Jacob M
IEEE Trans Comput Imaging
. 2023 Apr;
9:260-275.
PMID: 37090026
Computational imaging has been revolutionized by compressed sensing algorithms, which offer guaranteed uniqueness, convergence, and stability properties. Model-based deep learning methods that combine imaging physics with learned regularization priors have...
13.
Zou Q, Priya S, Nagpal P, Jacob M
Bioengineering (Basel)
. 2023 Mar;
10(3).
PMID: 36978736
The main focus of this work is to introduce a single free-breathing and ungated imaging protocol to jointly estimate cardiac function and myocardial T1 maps. We reconstruct a time series...
14.
Aggarwal H, Pramanik A, John M, Jacob M
IEEE Trans Med Imaging
. 2022 Nov;
42(4):1133-1144.
PMID: 36417742
Image reconstruction using deep learning algorithms offers improved reconstruction quality and lower reconstruction time than classical compressed sensing and model-based algorithms. Unfortunately, clean and fully sampled ground-truth data to train...
15.
Zou Q, Ahmed A, Nagpal P, Priya S, Schulte R, Jacob M
IEEE Trans Med Imaging
. 2022 Jul;
41(12):3552-3561.
PMID: 35816534
Current deep learning-based manifold learning algorithms such as the variational autoencoder (VAE) require fully sampled data to learn the probability density of real-world datasets. However, fully sampled data is often...
16.
Zou Q, Torres L, Fain S, Higano N, Bates A, Jacob M
Phys Med Biol
. 2022 Jun;
67(14).
PMID: 35714617
. We introduce an unsupervised motion-compensated reconstruction scheme for high-resolution free-breathing pulmonary magnetic resonance imaging.. We model the image frames in the time series as the deformed version of the...
17.
Ahmed A, Zou Q, Nagpal P, Jacob M
IEEE Trans Med Imaging
. 2022 Apr;
41(10):2693-2703.
PMID: 35436187
Bilinear models such as low-rank and dictionary methods, which decompose dynamic data to spatial and temporal factor matrices are powerful and memory-efficient tools for the recovery of dynamic MRI data....
18.
Jacob M, Mani M, Ye J
IEEE Signal Process Mag
. 2022 Jan;
37(1):54-68.
PMID: 35027816
In this survey, we provide a detailed review of recent advances in the recovery of continuous domain multidimensional signals from their few non-uniform (multichannel) measurements using structured low-rank matrix completion...
19.
Mani M, Yang B, Bathla G, Magnotta V, Jacob M
Magn Reson Med
. 2021 Nov;
87(4):1799-1815.
PMID: 34825729
Purpose: To propose a new method for the recovery of combined in-plane- and multi-band (MB)-accelerated diffusion MRI data. Methods: Combining MB acceleration with in-plane acceleration is crucial to improve the...
20.
Ahmed A, Nagpal P, Kruger S, Jacob M
Proc IEEE Int Symp Biomed Imaging
. 2021 Oct;
2021:1099-1102.
PMID: 34691363
Bilinear models such as low-rank and compressed sensing, which decompose the dynamic data to spatial and temporal factors, are powerful and memory efficient tools for the recovery of dynamic MRI...