What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Neuroscience
- Machine learning
Stamatios N. Sotiropoulos focuses on Diffusion MRI, Artificial intelligence, Connectome, Human Connectome Project and Neuroimaging.
Stamatios N. Sotiropoulos works mostly in the field of Diffusion MRI, limiting it down to concerns involving Data mining and, occasionally, Cortical surface, Preprocessor and Human Connectome.
His research integrates issues of Tractography, Computer vision and Pattern recognition in his study of Artificial intelligence.
His Connectome research is multidisciplinary, relying on both Simulation, Human brain and Mr imaging.
In his research on the topic of Human Connectome Project, Nerve tract, Heritability, Evolutionary biology and Twin study is strongly related with Fractional anisotropy.
His study explores the link between Neuroimaging and topics such as Biobank that cross with problems in Image processing, Fluid-attenuated inversion recovery and Medical physics.
His most cited work include:
- The minimal preprocessing pipelines for the Human Connectome Project. (2200 citations)
- An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging (1224 citations)
- Multimodal population brain imaging in the UK Biobank prospective epidemiological study (676 citations)
What are the main themes of his work throughout his whole career to date?
Diffusion MRI, Artificial intelligence, Human Connectome Project, Tractography and White matter are his primary areas of study.
His work deals with themes such as Deconvolution, Data mining, Connectome, Orientation and Voxel, which intersect with Diffusion MRI.
His Connectome research incorporates themes from Evolutionary biology and Simulation.
His Artificial intelligence study integrates concerns from other disciplines, such as Machine learning, Diffusion Tractography, Computer vision and Pattern recognition.
His Human Connectome Project study incorporates themes from Macaque, Data-driven, Cortical surface, Neuroimaging and Human brain.
His Tractography study deals with Neuroanatomy intersecting with Computational biology.
He most often published in these fields:
- Diffusion MRI (70.55%)
- Artificial intelligence (50.00%)
- Human Connectome Project (59.59%)
What were the highlights of his more recent work (between 2019-2021)?
- Human Connectome Project (59.59%)
- Diffusion MRI (70.55%)
- Artificial intelligence (50.00%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Human Connectome Project, Diffusion MRI, Artificial intelligence, White matter and Tractography.
Stamatios N. Sotiropoulos combines subjects such as Statistical physics, Orbit and Similarity with his study of Human Connectome Project.
His Diffusion MRI research is multidisciplinary, incorporating elements of Data-driven, Connectome and Encoding.
His Connectome research includes elements of Neuroimaging, Orientation, Resting state fMRI and Diffusion Tractography.
His studies deal with areas such as Heteroscedasticity and Pattern recognition as well as Artificial intelligence.
His Tractography research integrates issues from Channel, Parallel imaging, Human brain and Macaque.
Between 2019 and 2021, his most popular works were:
- XTRACT - Standardised protocols for automated tractography in the human and macaque brain. (25 citations)
- XTRACT - Standardised protocols for automated tractography in the human and macaque brain. (25 citations)
- XTRACT - Standardised protocols for automated tractography in the human and macaque brain. (25 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Neuroscience
Stamatios N. Sotiropoulos mostly deals with Tractography, Artificial intelligence, Human Connectome Project, Diffusion MRI and Macaque.
Stamatios N. Sotiropoulos interconnects Uncertainty quantification, Interpretability, Deep learning and Bayesian inference in the investigation of issues within Tractography.
The various areas that Stamatios N. Sotiropoulos examines in his Artificial intelligence study include Multivariate statistics and Pattern recognition.
His work on Canonical correlation as part of general Pattern recognition study is frequently linked to Sample size determination, therefore connecting diverse disciplines of science.
The Human Connectome Project study combines topics in areas such as White matter, Neuroanatomy, Human brain, Parallel imaging and Computational biology.
His biological study spans a wide range of topics, including Connectome, Pulse sequence, Cortical surface, Channel and Resting state fMRI.
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