4 citations · 9 across the 5 of their papers we have counts for
5 papers
Multi-scale MRI reconstruction via dilated ensemble networks
Wendi Ma, Marlon Bran Lorenzana, Wei Dai +2
As aliasing artefacts are highly structural and non-local, many MRI reconstruction networks use pooling to enlarge filter coverage and incorporate global context. However, this ina…
Single Image Compressed Sensing MRI via a Self-Supervised Deep Denoising Approach
Marlon Bran Lorenzana, Feng Liu, Shekhar S. Chandra
Popular methods in compressed sensing (CS) are dependent on deep learning (DL), where large amounts of data are used to train non-linear reconstruction models. However, ensuring ge…
Fractal Compressive Sensing
Marlon Bran Lorenzana, Benjamin Cottier, Matthew Marques +2
This paper introduces a sparse projection matrix composed of discrete (digital) periodic lines that create a pseudo-random (p.frac) sampling scheme. Our approach enables random Car…
AliasNet: Alias Artefact Suppression Network for Accelerated Phase-Encode MRI
Marlon E. Bran Lorenzana, Shekhar S. Chandra, Feng Liu
Sparse reconstruction is an important aspect of MRI, helping to reduce acquisition time and improve spatial-temporal resolution. Popular methods are based mostly on compressed sens…
Transformer Compressed Sensing via Global Image Tokens
Marlon Bran Lorenzana, Craig Engstrom, Shekhar S. Chandra
Convolutional neural networks (CNN) have demonstrated outstanding Compressed Sensing (CS) performance compared to traditional, hand-crafted methods. However, they are broadly limit…