64 citations · 89 across the 16 of their papers we have counts for
5 papers · 1 filter
Deep Generalization of Structured Low-Rank Algorithms (Deep-SLR)
Aniket Pramanik, Hemant Aggarwal, Mathews Jacob
Structured low-rank (SLR) algorithms, which exploit annihilation relations between the Fourier samples of a signal resulting from different properties, is a powerful image reconstr…
Calibrationless Parallel MRI using Model based Deep Learning (C-MODL)
Aniket Pramanik, Hemant Aggarwal, Mathews Jacob
We introduce a fast model based deep learning approach for calibrationless parallel MRI reconstruction. The proposed scheme is a non-linear generalization of structured low rank (S…
Off-the-grid model based deep learning (O-MODL)
Aniket Pramanik, Hemant Kumar Aggarwal, Mathews Jacob
We introduce a model based off-the-grid image reconstruction algorithm using deep learned priors. The main difference of the proposed scheme with current deep learning strategies i…
Model-based free-breathing cardiac MRI reconstruction using deep learned \& STORM priors: MoDL-STORM
Sampurna Biswas, Hemant K. Aggarwal, Sunrita Poddar +1
We introduce a model-based reconstruction framework with deep learned (DL) and smoothness regularization on manifolds (STORM) priors to recover free breathing and ungated (FBU) car…
Clustering of Data with Missing Entries
Sunrita Poddar, Mathews Jacob
The analysis of large datasets is often complicated by the presence of missing entries, mainly because most of the current machine learning algorithms are designed to work with ful…