Literature DB >> 31350164

Ultimate MRI.

Lawrence L Wald1.   

Abstract

The basic principles of Magnetic Resonance have been understood for over 70 years and a mainstay of medical imaging for over 40. At this point, it's no longer about simply porting these principles to medical imaging. But we are by no means confined to simply polishing either. Significant innovation and even revolution can come to old technologies. The recent revolution in optical microscopy shattered the resolution constraint imposed by a seemingly fundamental physical law (the diffraction limit) and reinvigorated a 500-year-old modality. Progress comes from re-examining old-ways and sidestepping underlying assumptions. This is already underway for MRI; and is fueled by advances in image reconstruction. Reconstruction increasingly employs sophisticated general models often using subtle and hopefully innocuous prior knowledge about the object. This allows a careful re-examination of some basic prerequisites for MRI such as uniform static fields, linear encoding fields, full Nyquist sampling, or even a stationary object. These powerful reconstruction tools are driving changes in acquisition strategy and basic hardware. The scanner of the future will know more about itself and its patient and his/her biology than ever before. This strategy emboldens relaxed hardware constraints and more specialized scanners, hopefully expanding the reach and value offered by MR imaging.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Future systems; Image reconstruction; MRI optimization; Magnetic resonance imaging technology

Year:  2019        PMID: 31350164      PMCID: PMC6708442          DOI: 10.1016/j.jmr.2019.07.016

Source DB:  PubMed          Journal:  J Magn Reson        ISSN: 1090-7807            Impact factor:   2.229


  50 in total

1.  Iterative reconstruction of single-shot spiral MRI with off resonance.

Authors:  T B Harshbarger; D B Twieg
Journal:  IEEE Trans Med Imaging       Date:  1999-03       Impact factor: 10.048

2.  SENSE: sensitivity encoding for fast MRI.

Authors:  K P Pruessmann; M Weiger; M B Scheidegger; P Boesiger
Journal:  Magn Reson Med       Date:  1999-11       Impact factor: 4.668

3.  3D imaging with a single-sided sensor: an open tomograph.

Authors:  J Perlo; F Casanova; B Blümich
Journal:  J Magn Reson       Date:  2004-02       Impact factor: 2.229

4.  Controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA) for multi-slice imaging.

Authors:  Felix A Breuer; Martin Blaimer; Robin M Heidemann; Matthias F Mueller; Mark A Griswold; Peter M Jakob
Journal:  Magn Reson Med       Date:  2005-03       Impact factor: 4.668

5.  Spatially encoded NMR and the acquisition of 2D magnetic resonance images within a single scan.

Authors:  Yoav Shrot; Lucio Frydman
Journal:  J Magn Reson       Date:  2005-02       Impact factor: 2.229

6.  Controlled aliasing in volumetric parallel imaging (2D CAIPIRINHA).

Authors:  Felix A Breuer; Martin Blaimer; Matthias F Mueller; Nicole Seiberlich; Robin M Heidemann; Mark A Griswold; Peter M Jakob
Journal:  Magn Reson Med       Date:  2006-03       Impact factor: 4.668

Review 7.  A review of methods for correction of intensity inhomogeneity in MRI.

Authors:  Uros Vovk; Franjo Pernus; Bostjan Likar
Journal:  IEEE Trans Med Imaging       Date:  2007-03       Impact factor: 10.048

8.  Sparse MRI: The application of compressed sensing for rapid MR imaging.

Authors:  Michael Lustig; David Donoho; John M Pauly
Journal:  Magn Reson Med       Date:  2007-12       Impact factor: 4.668

9.  Augmented generalized SENSE reconstruction to correct for rigid body motion.

Authors:  Roland Bammer; Murat Aksoy; Chunlei Liu
Journal:  Magn Reson Med       Date:  2007-01       Impact factor: 4.668

10.  Automatic compensation of motion artifacts in MRI.

Authors:  D Atkinson; D L Hill; P N Stoyle; P E Summers; S Clare; R Bowtell; S F Keevil
Journal:  Magn Reson Med       Date:  1999-01       Impact factor: 4.668

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  7 in total

1.  MRI radiomics in the prediction of the volumetric response in meningiomas after gamma knife radiosurgery.

Authors:  Herwin Speckter; Marko Radulovic; Kire Trivodaliev; Velicko Vranes; Johanna Joaquin; Wenceslao Hernandez; Angel Mota; Jose Bido; Giancarlo Hernandez; Diones Rivera; Luis Suazo; Santiago Valenzuela; Peter Stoeter
Journal:  J Neurooncol       Date:  2022-06-17       Impact factor: 4.506

2.  Investigation of changes in the activity and function of dry eye-associated brain regions using the amplitude of low-frequency fluctuations method.

Authors:  Tie Sun; Hui-Ye Shu; Jie-Li Wu; Ting Su; Yu-Ji Liu; Li-Juan Zhang; Qiu-Yu Li; Yi-Cong Pan; Qian-Min Ge; Yi Shao
Journal:  Biosci Rep       Date:  2022-01-28       Impact factor: 3.840

3.  Reducing the Complexity of Model-Based MRI Reconstructions via Sparsification.

Authors:  Alex Gutierrez; Michael Mullen; Di Xiao; Albert Jang; Taylor Froelich; Michael Garwood; Jarvis Haupt
Journal:  IEEE Trans Med Imaging       Date:  2021-08-31       Impact factor: 11.037

Review 4.  Volume Reduction Techniques for the Classification of Independent Components of rs-fMRI Data: a Study with Convolutional Neural Networks.

Authors:  Leonel Mera Jiménez; John F Ochoa Gómez
Journal:  Neuroinformatics       Date:  2021-04-07

5.  Free induction decay navigator motion metrics for prediction of diagnostic image quality in pediatric MRI.

Authors:  Tess E Wallace; Onur Afacan; Camilo Jaimes; Joanne Rispoli; Kristina Pelkola; Monet Dugan; Tobias Kober; Simon K Warfield
Journal:  Magn Reson Med       Date:  2021-01-06       Impact factor: 4.668

6.  Effects of iron oxide nanoparticles as T2-MRI contrast agents on reproductive system in male mice.

Authors:  Heyu Yang; Hui Wang; Chenghao Wen; Shun Bai; Pengfei Wei; Bo Xu; Yunjun Xu; Chaozhao Liang; Yunjiao Zhang; Guilong Zhang; Huiqin Wen; Li Zhang
Journal:  J Nanobiotechnology       Date:  2022-03-02       Impact factor: 10.435

7.  Deep learning for fast low-field MRI acquisitions.

Authors:  Reina Ayde; Tobias Senft; Najat Salameh; Mathieu Sarracanie
Journal:  Sci Rep       Date:  2022-07-06       Impact factor: 4.996

  7 in total

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