2014 - Fellow of the Indian National Academy of Engineering (INAE)
His primary scientific interests are in Nuclear magnetic resonance, Artificial intelligence, Computer vision, Magnetic resonance imaging and Imaging phantom. His Nuclear magnetic resonance research incorporates themes from Image resolution, Optics, Excitation and Magnetization. His work in Iterative reconstruction and Compressed sensing is related to Artificial intelligence.
The Compressed sensing study combines topics in areas such as Wavelet, Pattern recognition, Parallel imaging and Undersampling. His Computer vision research is multidisciplinary, incorporating elements of Distortion, Diffusion MRI, Encoding and Spiral. His work on Mr imaging as part of general Magnetic resonance imaging study is frequently linked to Biofeedback, bridging the gap between disciplines.
Nuclear magnetic resonance, Magnetic resonance imaging, Artificial intelligence, Optics and Computer vision are his primary areas of study. As part of the same scientific family, John M. Pauly usually focuses on Nuclear magnetic resonance, concentrating on Excitation and intersecting with Pulse. In his study, Nuclear medicine is inextricably linked to Image quality, which falls within the broad field of Magnetic resonance imaging.
Artificial intelligence is often connected to Pattern recognition in his work. His biological study spans a wide range of topics, including Spiral and Aliasing. His Compressed sensing study incorporates themes from Parallel imaging and Undersampling.
John M. Pauly mainly focuses on Artificial intelligence, Pattern recognition, Deep learning, Magnetic resonance imaging and Image quality. As part of his studies on Artificial intelligence, John M. Pauly often connects relevant subjects like Computer vision. The various areas that John M. Pauly examines in his Pattern recognition study include Ground truth and Noise.
His Deep learning study also includes fields such as
His main research concerns Artificial intelligence, Image quality, Pattern recognition, Deep learning and Nuclear medicine. His study on Artificial intelligence is mostly dedicated to connecting different topics, such as Machine learning. John M. Pauly focuses mostly in the field of Pattern recognition, narrowing it down to matters related to Noise and, in some cases, Aliasing and Manifold.
John M. Pauly interconnects Ground truth, Magnetic resonance imaging, Predictive modelling and Benchmark in the investigation of issues within Deep learning. John M. Pauly has researched Magnetic resonance imaging in several fields, including Internal medicine and Cancer metabolism. His Compressed sensing study introduces a deeper knowledge of Algorithm.
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Sparse MRI: The application of compressed sensing for rapid MR imaging.
Michael Lustig;David Donoho;John M. Pauly.
Magnetic Resonance in Medicine (2007)
Compressed Sensing MRI
M. Lustig;D.L. Donoho;J.M. Santos;J.M. Pauly.
IEEE Signal Processing Magazine (2008)
Control over brain activation and pain learned by using real-time functional MRI.
R. Christopher deCharms;Fumiko Maeda;Gary H. Glover;David Ludlow.
Proceedings of the National Academy of Sciences of the United States of America (2005)
Parameter relations for the Shinnar-Le Roux selective excitation pulse design algorithm (NMR imaging)
J. Pauly;P. Le Roux;D. Nishimura;A. Macovski.
IEEE Transactions on Medical Imaging (1991)
ESPIRiT--an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA.
Martin Uecker;Peng Lai;Mark J. Murphy;Patrick Virtue.
Magnetic Resonance in Medicine (2014)
A k-space analysis of small-tip-angle excitation
John Pauly;Dwight Nishimura;Albert Macovski.
Journal of Magnetic Resonance (1989)
SPIRiT: Iterative self-consistent parallel imaging reconstruction from arbitrary k-space.
Michael Lustig;Michael Lustig;John M. Pauly.
Magnetic Resonance in Medicine (2010)
Projection reconstruction techniques for reduction of motion effects in MRI.
G. H. Glover;J. M. Pauly.
Magnetic Resonance in Medicine (1992)
Simultaneous spatial and spectral selective excitation.
Meyer Ch;Pauly Jm;Macovski A;Nishimura Dg.
Magnetic Resonance in Medicine (1990)
Positive contrast magnetic resonance imaging of cells labeled with magnetic nanoparticles
Charles H. Cunningham;Takayasu Arai;Phillip C. Yang;Michael V. McConnell.
Magnetic Resonance in Medicine (2005)
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