What is he best known for?
The fields of study he is best known for:
- Internal medicine
- Magnetic resonance imaging
- Artificial intelligence
His scientific interests lie mostly in Diffusion MRI, White matter, Neuroscience, Magnetic resonance imaging and Anatomy.
His Diffusion MRI research integrates issues from Nuclear medicine, Brain mapping and Artificial intelligence.
His Artificial intelligence study integrates concerns from other disciplines, such as Computer vision and Pattern recognition.
His work on Association fiber as part of general White matter research is often related to Periventricular leukomalacia, thus linking different fields of science.
The Magnetic resonance imaging study combines topics in areas such as Large deformation diffeomorphic metric mapping and Neuroimaging.
Susumu Mori interconnects Superior longitudinal fasciculus, Iterative reconstruction and Corticospinal tract in the investigation of issues within Anatomy.
His most cited work include:
- Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. (2978 citations)
- Fiber tracking: Principles and strategies - A technical review (1702 citations)
- Fiber tract-based atlas of human white matter anatomy. (1643 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Diffusion MRI, Neuroscience, White matter, Magnetic resonance imaging and Artificial intelligence.
His research integrates issues of Brain mapping, Nuclear magnetic resonance and Anatomy in his study of Diffusion MRI.
His Neuroscience research incorporates themes from Huntington's disease and Brain morphometry.
His work in White matter addresses subjects such as Corpus callosum, which are connected to disciplines such as Internal capsule.
His work carried out in the field of Magnetic resonance imaging brings together such families of science as Brain atlas, In vivo and Pathology.
His Artificial intelligence research incorporates elements of Atlas, Atlas, Computer vision and Pattern recognition.
He most often published in these fields:
- Diffusion MRI (77.96%)
- Neuroscience (44.49%)
- White matter (44.09%)
What were the highlights of his more recent work (between 2015-2021)?
- Diffusion MRI (77.96%)
- Neuroscience (44.49%)
- Artificial intelligence (34.67%)
In recent papers he was focusing on the following fields of study:
Susumu Mori spends much of his time researching Diffusion MRI, Neuroscience, Artificial intelligence, White matter and Magnetic resonance imaging.
As a part of the same scientific study, Susumu Mori usually deals with the Diffusion MRI, concentrating on Pathology and frequently concerns with Brain size.
His Neuroscience study frequently draws connections between related disciplines such as Anatomy.
Susumu Mori has included themes like Atlas, Machine learning and Pattern recognition in his Artificial intelligence study.
His White matter research includes themes of Analysis of covariance, Correlation, Amyloid deposition, Globus pallidus and Cortex.
His Magnetic resonance imaging study integrates concerns from other disciplines, such as Hydrocephalus, Cardiology, Internal medicine, Dementia and Positron emission tomography.
Between 2015 and 2021, his most popular works were:
- Diffusion MRI fiber tractography of the brain (159 citations)
- Diffusion MRI fiber tractography of the brain (159 citations)
- The role of myelination in measures of white matter integrity: Combination of diffusion tensor imaging and two-photon microscopy of CLARITY intact brains. (86 citations)
In his most recent research, the most cited papers focused on:
- Internal medicine
- Artificial intelligence
- Magnetic resonance imaging
Diffusion MRI, White matter, Neuroscience, Brain segmentation and Artificial intelligence are his primary areas of study.
His work in the fields of Tractography overlaps with other areas such as Complex network.
His White matter study is concerned with the field of Magnetic resonance imaging as a whole.
His studies deal with areas such as Subventricular zone, Huntington's disease and Anatomy as well as Neuroscience.
His Brain segmentation research is multidisciplinary, relying on both Cognition, Atrophy, Data mining and Data set.
His studies in Artificial intelligence integrate themes in fields like Atlas, Atlas and Pattern recognition.
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