[HTML][HTML] Common artefacts encountered on images acquired with combined compressed sensing and SENSE

T Sartoretti, C Reischauer, E Sartoretti, C Binkert… - Insights into …, 2018 - Springer
Various techniques have been proposed which aim at scan time reduction and/or at
improved image quality by increasing the spatial resolution. Compressed sensing (CS) …

Reconstruction of multicontrast MR images through deep learning

WJ Do, S Seo, Y Han, JC Ye, SH Choi… - Medical …, 2020 - Wiley Online Library
Purpose Magnetic resonance (MR) imaging with a long scan time can lead to degraded
images due to patient motion, patient discomfort, and increased costs. For these reasons …

Experimental design for MRI by greedy policy search

T Bakker, H van Hoof, M Welling - Advances in Neural …, 2020 - proceedings.neurips.cc
In today's clinical practice, magnetic resonance imaging (MRI) is routinely accelerated
through subsampling of the associated Fourier domain. Currently, the construction of these …

Sparse reconstruction techniques in magnetic resonance imaging: methods, applications, and challenges to clinical adoption

AC Yang, M Kretzler, S Sudarski, V Gulani… - Investigative …, 2016 - journals.lww.com
The family of sparse reconstruction techniques, including the recently introduced
compressed sensing framework, has been extensively explored to reduce scan times in …

Image recovery via transform learning and low-rank modeling: The power of complementary regularizers

B Wen, Y Li, Y Bresler - IEEE Transactions on Image …, 2020 - ieeexplore.ieee.org
Recent works on adaptive sparse and on low-rank signal modeling have demonstrated their
usefulness in various image/video processing applications. Patch-based methods exploit …

Knee imaging: Rapid three‐dimensional fast spin‐echo using compressed sensing

R Kijowski, H Rosas, A Samsonov… - Journal of Magnetic …, 2017 - Wiley Online Library
Purpose To investigate the feasibility of using compressed sensing (CS) to accelerate three‐
dimensional fast spin‐echo (3D‐FSE) imaging of the knee. Materials and Methods A 3D …

A theoretical framework for self-supervised MR image reconstruction using sub-sampling via variable density Noisier2Noise

C Millard, M Chiew - IEEE transactions on computational …, 2023 - ieeexplore.ieee.org
In recent years, there has been attention on leveraging the statistical modeling capabilities
of neural networks for reconstructing sub-sampled Magnetic Resonance Imaging (MRI) data …

[HTML][HTML] Compressive sensing-based IoT applications: A review

H Djelouat, A Amira, F Bensaali - Journal of Sensor and Actuator …, 2018 - mdpi.com
The Internet of Things (IoT) holds great promises to provide an edge cutting technology that
enables numerous innovative services related to healthcare, manufacturing, smart cities and …

Hepatobiliary phase imaging in cirrhotic patients using compressed sensing and controlled aliasing in parallel imaging results in higher acceleration

S Yoon, YS Shim, SH Park, J Sung, MD Nickel… - European …, 2024 - Springer
Objective We aimed to compare the image quality and focal lesion detection ability of
hepatobiliary phase (HBP) images obtained using compressed sensing (CS) and controlled …

From compressed‐sensing to deep learning MR: Comparative biventricular cardiac function analysis in a patient cohort

X Yan, Y Luo, X Chen, EZ Chen, Q Liu… - Journal of Magnetic …, 2024 - Wiley Online Library
Background Conventional segmented, retrospectively gated cine (Conv‐cine) is challenged
in patients with breath‐hold difficulties. Compressed sensing (CS) has shown values in cine …