What is he best known for?
The fields of study he is best known for:
- Magnetic resonance imaging
- Artificial intelligence
- Optics
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.
His most cited work include:
- Sparse MRI: The application of compressed sensing for rapid MR imaging. (4863 citations)
- Compressed Sensing MRI (1440 citations)
- Parameter relations for the Shinnar-Le Roux selective excitation pulse design algorithm (NMR imaging) (694 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Nuclear magnetic resonance (37.27%)
- Magnetic resonance imaging (27.88%)
- Artificial intelligence (23.06%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (23.06%)
- Pattern recognition (5.36%)
- Deep learning (4.29%)
In recent papers he was focusing on the following fields of study:
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
- Leverage which connect with Pixel, Uncertainty quantification and Undersampling,
- Hallucinating which is related to area like Image restoration and Identification.
His work carried out in the field of Magnetic resonance imaging brings together such families of science as Internal medicine, Healthy control, Medical imaging, Scanner and Prostate cancer.
His work is dedicated to discovering how Image quality, Nuclear medicine are connected with Stage and other disciplines.
Between 2017 and 2021, his most popular works were:
- Deep Generative Adversarial Neural Networks for Compressive Sensing MRI (208 citations)
- Hyperpolarized 13C MRI: Path to Clinical Translation in Oncology (127 citations)
- Deep learning enables reduced gadolinium dose for contrast-enhanced brain MRI (92 citations)
In his most recent research, the most cited papers focused on:
- Magnetic resonance imaging
- Artificial intelligence
- Optics
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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