His primary scientific interests are in Diffusion MRI, Artificial intelligence, Magnetic resonance imaging, Neuroimaging and Neuroscience. His Diffusion MRI research includes elements of Image processing, Preprocessor, Data mining and Human Connectome Project. The concepts of his Artificial intelligence study are interwoven with issues in Tractography, Machine learning, Computer vision and Pattern recognition.
His Magnetic resonance imaging study combines topics from a wide range of disciplines, such as Human Connectome, Image registration and Algorithm. His biological study spans a wide range of topics, including Test and Neuroanatomy. His work on Prefrontal cortex, Functional magnetic resonance imaging and Multimodal imaging as part of general Neuroscience study is frequently linked to Data acquisition, bridging the gap between disciplines.
His main research concerns Diffusion MRI, Neuroscience, Artificial intelligence, Neuroimaging and Magnetic resonance imaging. His work carried out in the field of Diffusion MRI brings together such families of science as White matter, Nuclear magnetic resonance and Human Connectome Project. Within one scientific family, Jesper L. R. Andersson focuses on topics pertaining to Connectome under Human Connectome Project, and may sometimes address concerns connected to Simulation.
His Neuroscience research integrates issues from Classical conditioning and Cerebral blood flow. His work deals with themes such as Computer vision and Pattern recognition, which intersect with Artificial intelligence. His biological study deals with issues like Algorithm, which deal with fields such as Angular resolution.
Diffusion MRI, Human Connectome Project, White matter, Neuroimaging and Neuroscience are his primary areas of study. His research integrates issues of Algorithm, Brain activity and meditation and Biomedical engineering in his study of Diffusion MRI. His Human Connectome Project research is multidisciplinary, relying on both Resting state fMRI, Brain mapping and Artificial intelligence.
His Artificial intelligence research includes themes of Computer engineering and Pattern recognition. As a part of the same scientific family, Jesper L. R. Andersson mostly works in the field of Neuroimaging, focusing on Set and, on occasion, Statistical power and Gerontology. In general Neuroscience study, his work on Inferior parietal lobule and Default mode network often relates to the realm of Postmenstrual Age and Association, thereby connecting several areas of interest.
His primary areas of investigation include Diffusion MRI, Human Connectome Project, Pipeline, Data mining and Resting state fMRI. His Diffusion MRI research is multidisciplinary, incorporating perspectives in Algorithm, White matter and Elementary cognitive task. Jesper L. R. Andersson has included themes like Diffusion imaging, Robustness and Set in his Human Connectome Project study.
His Pipeline studies intersect with other disciplines such as Connectome, Image processing and Artificial intelligence. His Image processing research incorporates elements of Fluid-attenuated inversion recovery, Medical physics and Neuroimaging. His Resting state fMRI study integrates concerns from other disciplines, such as Young adult, Gerontology, Human Connectome and Connectomics.
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The minimal preprocessing pipelines for the Human Connectome Project.
Matthew F. Glasser;Stamatios N. Sotiropoulos;J. Anthony Wilson;Timothy S. Coalson.
A multi-modal parcellation of human cerebral cortex
Matthew F. Glasser;Timothy S. Coalson;Emma C. Robinson;Emma C. Robinson;Carl D. Hacker.
Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration.
Arno Klein;Jesper L. R. Andersson;Babak A. Ardekani;Babak A. Ardekani;John Ashburner.
How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging
Jesper L.R. Andersson;Stefan Skare;John Ashburner.
An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging
Jesper L.R. Andersson;Stamatios N. Sotiropoulos.
Valid conjunction inference with the minimum statistic.
Thomas E. Nichols;Matthew Brett;Jesper L. R. Andersson;Tor D. Wager.
Resting-state fMRI in the Human Connectome Project
S M Smith;C F Beckmann;J Andersson;E J Auerbach.
Multimodal population brain imaging in the UK Biobank prospective epidemiological study
Karla L Miller;Fidel Alfaro-Almagro;Neal K Bangerter;David L Thomas.
Nature Neuroscience (2016)
Modeling Geometric Deformations in EPI Time Series
Jesper L.R. Andersson;Chloe Hutton;John Ashburner;Robert Turner.
Advances in diffusion MRI acquisition and processing in the Human Connectome Project.
Stamatios N. Sotiropoulos;Saâd Jbabdi;Junqian Xu;Jesper L. R. Andersson.
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