Full utilization of conjugate symmetry: combining virtual conjugate coil reconstruction with partial Fourier imaging for gâfactor reduction in accelerated MRI
Sign Up to like & getrecommendations! Published in 2019 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.27799
Abstract: In this study we propose a method to combine the parallel virtual conjugate coil (VCC) reconstruction with partial Fourier (PF) acquisition to improve reconstruction conditioning and reduce noise amplification in accelerated MRI where PF is… read more here.
Keywords: reconstruction; virtual conjugate; conjugate; reconstruction partial ... See more keywords
Partial Fourier reconstruction of complex MR images using complex-valued convolutional neural networks.
Sign Up to like & getrecommendations! Published in 2021 at "Magnetic resonance in medicine"
DOI: 10.1002/mrm.29033
Abstract: PURPOSE To provide a complex-valued deep learning approach for partial Fourier (PF) reconstruction of complex MR images. METHODS Conventional PF reconstruction methods, such as projection onto convex sets (POCS), uses low-resolution image phase information from… read more here.
Keywords: reconstruction; phase; image; fourier reconstruction ... See more keywords
Accelerated electron paramagnetic resonance imaging using partial Fourier compressed sensing reconstruction.
Sign Up to like & getrecommendations! Published in 2017 at "Magnetic resonance imaging"
DOI: 10.1016/j.mri.2016.10.029
Abstract: PURPOSE Electron paramagnetic resonance (EPR) imaging has evolved as a promising tool to provide non-invasive assessment of tissue oxygenation levels. Due to the extremely short T2 relaxation time of electrons, single point imaging (SPI) is… read more here.
Keywords: reconstruction; electron paramagnetic; compressed sensing; resonance ... See more keywords
Analysis of a Deep Learning-Based Superresolution Algorithm Tailored to Partial Fourier Gradient Echo Sequences of the Abdomen at 1.5 T: Reduction of Breath-Hold Time and Improvement of Image Quality.
Sign Up to like & getrecommendations! Published in 2021 at "Investigative radiology"
DOI: 10.1097/rli.0000000000000825
Abstract: OBJECTIVES The aim of this study was to investigate the feasibility and impact of a novel deep learning superresolution algorithm tailored to partial Fourier allowing retrospectively theoretical acquisition time reduction in 1.5 T T1-weighted gradient… read more here.
Keywords: time; superresolution algorithm; image; deep learning ... See more keywords
Application of a Deep Learning Algorithm for Combined Super-Resolution and Partial Fourier Reconstruction Including Time Reduction in T1-Weighted Precontrast and Postcontrast Gradient Echo Imaging of Abdominopelvic MR Imaging
Sign Up to like & getrecommendations! Published in 2022 at "Diagnostics"
DOI: 10.3390/diagnostics12102370
Abstract: Purpose: The purpose of this study was to test the technical feasibility and the impact on the image quality of a deep learning-based super-resolution reconstruction algorithm in 1.5 T abdominopelvic MR imaging. Methods: 44 patients… read more here.
Keywords: partial fourier; super resolution; reconstruction; deep learning ... See more keywords