1 citations · 2 across the 2 of their papers we have counts for
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Motion-Informed Deep Learning for Brain MR Image Reconstruction Framework
Zhifeng Chen, Kamlesh Pawar, Kh Tohidul Islam +3
Motion artifacts in Magnetic Resonance Imaging (MRI) are one of the frequently occurring artifacts due to patient movements during scanning. Motion is estimated to be present in ap…
PixCUE: Joint Uncertainty Estimation and Image Reconstruction in MRI using Deep Pixel Classification
Mevan Ekanayake, Kamlesh Pawar, Gary Egan +1
Deep learning (DL) models are capable of successfully exploiting latent representations in MR data and have become state-of-the-art for accelerated MRI reconstruction. However, und…
MoCoNet: Motion Correction in 3D MPRAGE images using a Convolutional Neural Network approach
Kamlesh Pawar, Zhaolin Chen, N. Jon Shah +1
Purpose: The suppression of motion artefacts from MR images is a challenging task. The purpose of this paper is to develop a standalone novel technique to suppress motion artefacts…