H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 33 Citations 5,472 104 World Ranking 6594 National Ranking 317

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Magnetic resonance imaging
  • Computer vision

Maxim Zaitsev mostly deals with Computer vision, Artificial intelligence, Magnetic resonance imaging, Nuclear medicine and Motion. His Tracking system, Image processing and Motion capture study in the realm of Computer vision connects with subjects such as Context and Electromagnetic field. His studies deal with areas such as Signal and Curvilinear coordinates as well as Artificial intelligence.

Maxim Zaitsev has included themes like Tracking, Pathological, Neuroimaging and Anatomy in his Magnetic resonance imaging study. His Nuclear medicine research is multidisciplinary, incorporating elements of Image quality, Visualization, Rendering and Velocity mapping. Maxim Zaitsev combines subjects such as Motion artifacts, Prospective motion correction and Magnetosphere particle motion with his study of Motion.

His most cited work include:

  • Time-resolved 3D MR velocity mapping at 3T: Improved navigator-gated assessment of vascular anatomy and blood flow (327 citations)
  • Magnetic resonance imaging of freely moving objects: prospective real-time motion correction using an external optical motion tracking system. (324 citations)
  • Point spread function mapping with parallel imaging techniques and high acceleration factors: fast, robust, and flexible method for echo-planar imaging distortion correction. (310 citations)

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

Maxim Zaitsev spends much of his time researching Artificial intelligence, Computer vision, Magnetic resonance imaging, Nuclear magnetic resonance and Imaging phantom. Artificial intelligence and Data acquisition are frequently intertwined in his study. His Computer vision study combines topics from a wide range of disciplines, such as Phase, Robustness and Encoding.

His Magnetic resonance imaging research integrates issues from Tracking, Anatomy, Neuroimaging and Motion artifacts. His work focuses on many connections between Imaging phantom and other disciplines, such as Voxel, that overlap with his field of interest in Excitation. His work carried out in the field of Image quality brings together such families of science as Image processing and Match moving.

He most often published in these fields:

  • Artificial intelligence (41.43%)
  • Computer vision (41.43%)
  • Magnetic resonance imaging (20.95%)

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

  • Electromagnetic coil (13.33%)
  • Algorithm (17.14%)
  • Acoustics (9.52%)

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

The scientist’s investigation covers issues in Electromagnetic coil, Algorithm, Acoustics, Multi coil and Shim. His Algorithm research is multidisciplinary, incorporating perspectives in Image quality, Phase, Imaging phantom, Signal and Iterative reconstruction. His Image quality research incorporates elements of Echo, Tracking, Match moving, Dropout and Artifact.

His study in Imaging phantom is interdisciplinary in nature, drawing from both Motion, Nyquist–Shannon sampling theorem, Oversampling and Rotation. His study looks at the relationship between Acoustics and topics such as Shielded cable, which overlap with Optics. His work deals with themes such as Magnetic resonance imaging, Harmonic analysis and Mathematical optimization, which intersect with Topology.

Between 2017 and 2021, his most popular works were:

  • Development and implementation of an 84-channel matrix gradient coil (20 citations)
  • Pulseq-Graphical Programming Interface: Open source visual environment for prototyping pulse sequences and integrated magnetic resonance imaging algorithm development. (11 citations)
  • A 32-channel multi-coil setup optimized for human brain shimming at 9.4T. (6 citations)

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

  • Artificial intelligence
  • Magnetic resonance imaging
  • Algorithm

His main research concerns Scanner, Electromagnetic coil, Algorithm, Acoustics and Multi coil. His Scanner study incorporates themes from Visual programming language, Engineering drawing, Schematic and Signal processing. His Algorithm study combines topics in areas such as Image quality, Python, Image processing, Undersampling and Parallel imaging.

Maxim Zaitsev has researched Acoustics in several fields, including Encoding, Eddy current and Shielded cable. His Multi coil research includes elements of Anatomy, Shim, Spherical harmonics and Coil array. His research integrates issues of Singular value decomposition, Cross-validation, Communication channel and Amplifier in his study of Shim.

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.

Top Publications

Time-resolved 3D MR velocity mapping at 3T: Improved navigator-gated assessment of vascular anatomy and blood flow

Michael Markl;Andreas Harloff;Thorsten A. Bley;Maxim Zaitsev.
Journal of Magnetic Resonance Imaging (2007)

447 Citations

Magnetic resonance imaging of freely moving objects: prospective real-time motion correction using an external optical motion tracking system.

Maxim Zaitsev;Christian Dold;Georgios Sakas;Jürgen Hennig.
NeuroImage (2006)

403 Citations

Point spread function mapping with parallel imaging techniques and high acceleration factors: fast, robust, and flexible method for echo-planar imaging distortion correction.

M. Zaitsev;J. Hennig;O. Speck.
Magnetic Resonance in Medicine (2004)

362 Citations

Motion artifacts in MRI: A complex problem with many partial solutions.

Maxim Zaitsev;Julian Maclaren;Michael Herbst.
Journal of Magnetic Resonance Imaging (2015)

347 Citations

Prospective motion correction in brain imaging: a review.

Julian Maclaren;Michael Herbst;Oliver Speck;Maxim Zaitsev.
Magnetic Resonance in Medicine (2013)

323 Citations

Parallel imaging in non-bijective, curvilinear magnetic field gradients: a concept study.

Jürgen Hennig;Anna Masako Welz;Gerrit Schultz;Jan G. Korvink.
Magnetic Resonance Materials in Physics Biology and Medicine (2008)

188 Citations

Measurement and correction of microscopic head motion during magnetic resonance imaging of the brain.

Julian Maclaren;Brian S. R. Armstrong;Robert T. Barrows;K. A. Danishad.
PLOS ONE (2012)

180 Citations

Prospective real-time slice-by-slice motion correction for fMRI in freely moving subjects.

O. Speck;J. Hennig;M. Zaitsev.
Magnetic Resonance Materials in Physics Biology and Medicine (2006)

155 Citations

Highest Resolution In Vivo Human Brain MRI Using Prospective Motion Correction

Daniel Stucht;K. Appu Danishad;Peter Schulze;Frank Godenschweger.
PLOS ONE (2015)

148 Citations

Time-resolved, 3-dimensional magnetic resonance flow analysis at 3 T: visualization of normal and pathological aortic vascular hemodynamics.

Alex Frydrychowicz;Andreas Harloff;Bernd Jung;Maxim Zaitsev.
Journal of Computer Assisted Tomography (2007)

138 Citations

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

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