D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 88 Citations 25,716 375 World Ranking 69 National Ranking 36

Research.com Recognitions

Awards & Achievements

2019 - Fellow, National Academy of Inventors

2012 - Fellow of the Indian National Academy of Engineering (INAE)

Overview

What is he best known for?

The fields of study he is best known for:

  • Magnetic resonance imaging
  • Artificial intelligence
  • Internal medicine

His primary scientific interests are in Nuclear magnetic resonance, Artificial intelligence, Magnetic resonance imaging, Electromagnetic coil and Computer vision. His Nuclear magnetic resonance study incorporates themes from Phased array, Imaging phantom, Excitation, Scanner and Voxel. His research in Voxel intersects with topics in Aliasing and Artifact.

His studies in Artificial intelligence integrate themes in fields like Diffusion MRI, Connectome and Pattern recognition. His Magnetic resonance imaging research includes themes of Sensitivity, Neuroimaging, Resting state fMRI, Neuroscience and Resolution. His Electromagnetic coil research is multidisciplinary, incorporating perspectives in Noise and Optics.

His most cited work include:

  • Blipped-controlled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced g-factor penalty. (880 citations)
  • Blipped-controlled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced g-factor penalty. (880 citations)
  • Comparison of physiological noise at 1.5 T, 3 T and 7 T and optimization of fMRI acquisition parameters. (490 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of study are Nuclear magnetic resonance, Magnetic resonance imaging, Artificial intelligence, Electromagnetic coil and Computer vision. His Nuclear magnetic resonance research integrates issues from Phase, Optics, Excitation, Radiofrequency coil and Specific absorption rate. In his study, which falls under the umbrella issue of Magnetic resonance imaging, White matter is strongly linked to Neuroscience.

His Artificial intelligence research is multidisciplinary, relying on both Diffusion MRI and Pattern recognition. His work deals with themes such as Acoustics, Phased array, Imaging phantom, Noise and Biomedical engineering, which intersect with Electromagnetic coil. His Computer vision research includes elements of Sampling and Signal.

He most often published in these fields:

  • Nuclear magnetic resonance (40.55%)
  • Magnetic resonance imaging (33.39%)
  • Artificial intelligence (31.74%)

What were the highlights of his more recent work (between 2017-2021)?

  • Biomedical engineering (18.17%)
  • Electromagnetic coil (31.93%)
  • Magnetic resonance imaging (33.39%)

In recent papers he was focusing on the following fields of study:

His primary areas of investigation include Biomedical engineering, Electromagnetic coil, Magnetic resonance imaging, Scanner and Artificial intelligence. His Biomedical engineering research is multidisciplinary, incorporating elements of Deep brain stimulation, Imaging phantom, Dielectric heating, Neuroimaging and Human brain. Lawrence L. Wald combines subjects such as White matter, Array coil, Functional neuroimaging and Nuclear magnetic resonance with his study of Human brain.

His research integrates issues of Acoustics, Pulse generator, Fast mri, Position and Healthy subjects in his study of Electromagnetic coil. Within one scientific family, Lawrence L. Wald focuses on topics pertaining to Image resolution under Magnetic resonance imaging, and may sometimes address concerns connected to Demagnetizing field and Magnetic resonance imaging of the brain. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Computer vision and Pattern recognition.

Between 2017 and 2021, his most popular works were:

  • Hyperpolarized 13C MRI: Path to Clinical Translation in Oncology (127 citations)
  • High-resolution in vivo diffusion imaging of the human brain with generalized slice dithered enhanced resolution: Simultaneous multislice (gSlider-SMS) (87 citations)
  • Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling. (66 citations)

In his most recent research, the most cited papers focused on:

  • Magnetic resonance imaging
  • Artificial intelligence
  • Internal medicine

Lawrence L. Wald mostly deals with Biomedical engineering, Artificial intelligence, Encoding, Computer vision and Electromagnetic coil. He has researched Biomedical engineering in several fields, including Lead, Deep brain stimulation, Imaging phantom, Dielectric heating and Radiofrequency coil. His work on Artificial intelligence is being expanded to include thematically relevant topics such as Magnetic resonance imaging.

His research integrates issues of Sampling, Trajectory and Aliasing in his study of Encoding. Lawrence L. Wald works mostly in the field of Computer vision, limiting it down to topics relating to Dither and, in certain cases, Regularization, Connectome, Visualization and Nuclear magnetic resonance. The Nuclear magnetic resonance study combines topics in areas such as Acoustics and Magnet.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Blipped-controlled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced g-factor penalty.

Kawin Setsompop;Borjan A. Gagoski;Jonathan R. Polimeni;Thomas Witzel;Thomas Witzel.
Magnetic Resonance in Medicine (2012)

1093 Citations

Comparison of physiological noise at 1.5 T, 3 T and 7 T and optimization of fMRI acquisition parameters.

Christina Triantafyllou;Richard D. Hoge;Gunnar Krueger;Christopher J. Wiggins.
NeuroImage (2005)

621 Citations

A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI

Juan Eugenio Iglesias;Jean C. Augustinack;Khoa Nguyen;Christopher M. Player.
NeuroImage (2015)

534 Citations

Automated segmentation of hippocampal subfields from ultra‐high resolution in vivo MRI

Koen Van Leemput;Koen Van Leemput;Akram Bakkour;Thomas Benner;Graham Wiggins.
Hippocampus (2009)

418 Citations

Visual word processing and experiential origins of functional selectivity in human extrastriate cortex

Chris I. Baker;Jia Liu;Lawrence L. Wald;Kenneth K. Kwong.
Proceedings of the National Academy of Sciences of the United States of America (2007)

382 Citations

Pushing the limits of in vivo diffusion MRI for the Human Connectome Project

K. Setsompop;R. Kimmlingen;E. Eberlein;T. Witzel.
NeuroImage (2013)

379 Citations

32-channel 3 Tesla receive-only phased-array head coil with soccer-ball element geometry.

G.C. Wiggins;C. Triantafyllou;A. Potthast;A. Reykowski.
Magnetic Resonance in Medicine (2006)

367 Citations

Theory and application of array coils in MR spectroscopy

Steven M. Wright;Lawrence L. Wald;Lawrence L. Wald.
NMR in Biomedicine (1997)

355 Citations

Stereopsis activates V3A and caudal intraparietal areas in macaques and humans

Doris Y. Tsao;Wim Vanduffel;Wim Vanduffel;Yuka Sasaki;Denis Fize.
Neuron (2003)

331 Citations

Laminar analysis of 7 T BOLD using an imposed spatial activation pattern in human V1

Jonathan R. Polimeni;Bruce Fischl;Bruce Fischl;Douglas N. Greve;Lawrence L. Wald;Lawrence L. Wald.
NeuroImage (2010)

330 Citations

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Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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