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eess.IV2023
Adapting model-based deep learning to multiple acquisition conditions: Ada-MoDL
Aniket Pramanik, Sampada Bhave, Saurav Sajib +2
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 mult…
eess.IV2021★ 2 cited
Joint Calibrationless Reconstruction and Segmentation of Parallel MRI
Aniket Pramanik, Xiaodong Wu, Mathews Jacob
The volume estimation of brain regions from MRI data is a key problem in many clinical applications, where the acquisition of data at high spatial resolution is desirable. While pa…
eess.IV2021
Reconstruction and Segmentation of Parallel MR Data using Image Domain DEEP-SLR
Aniket Pramanik, Mathews Jacob
The main focus of this work is a novel framework for the joint reconstruction and segmentation of parallel MRI (PMRI) brain data. We introduce an image domain deep network for cali…