2019 - IEEE Fellow For contributions to medical imaging
His scientific interests lie mostly in Magnetic resonance imaging, Artificial intelligence, Computer vision, Segmentation and White matter. His Magnetic resonance imaging study combines topics from a wide range of disciplines, such as Nuclear medicine, Cerebrospinal fluid and Pediatrics. His work deals with themes such as Expectation–maximization algorithm, Atlas, Diffusion MRI and Pattern recognition, which intersect with Artificial intelligence.
His studies in Computer vision integrate themes in fields like Algorithm, Surface, Finite element method and Affine transformation. In his research, Probabilistic logic is intimately related to Ground truth, which falls under the overarching field of Segmentation. In his study, Surgery and Cerebellum is inextricably linked to Central nervous system, which falls within the broad field of White matter.
Artificial intelligence, Computer vision, Magnetic resonance imaging, Diffusion MRI and Segmentation are his primary areas of study. His Artificial intelligence study combines topics in areas such as Algorithm and Pattern recognition. His study in Pattern recognition is interdisciplinary in nature, drawing from both Deep learning and Expectation–maximization algorithm.
His Computer vision research is multidisciplinary, incorporating perspectives in Finite element method and Medical imaging. Simon K. Warfield studies White matter which is a part of Magnetic resonance imaging. His specific area of interest is Segmentation, where Simon K. Warfield studies Scale-space segmentation.
Simon K. Warfield mostly deals with Artificial intelligence, Magnetic resonance imaging, Diffusion MRI, Image quality and Computer vision. His Artificial intelligence research includes elements of Machine learning and Pattern recognition. Simon K. Warfield combines subjects such as Scale and Nuclear magnetic resonance with his study of Magnetic resonance imaging.
His Diffusion MRI research is multidisciplinary, incorporating elements of White matter and Nuclear medicine. In his work, Fourier transform is strongly intertwined with Isotropy, which is a subfield of Computer vision. Image segmentation is a subfield of Segmentation that Simon K. Warfield studies.
Simon K. Warfield spends much of his time researching Artificial intelligence, Diffusion MRI, Deep learning, Fractional anisotropy and Anatomy. His Artificial intelligence research includes themes of Machine learning and Computer vision. His study looks at the intersection of Diffusion MRI and topics like White matter with Tuberous sclerosis, Nuclear medicine and Everolimus.
His Deep learning research incorporates themes from Subject-matter expert, Image and Convolutional neural network, Pattern recognition. His work in the fields of Pattern recognition, such as Segmentation, overlaps with other areas such as Data modeling. His studies deal with areas such as Audiology, Corpus callosum, Autism, Autism spectrum disorder and Biomedical engineering as well as Fractional anisotropy.
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Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation
S.K. Warfield;K.H. Zou;W.M. Wells.
IEEE Transactions on Medical Imaging (2004)
Statistical validation of image segmentation quality based on a spatial overlap index.
Kelly H. Zou;Kelly H. Zou;Simon K. Warfield;Aditya Bharatha;Clare M.C. Tempany.
Academic Radiology (2004)
Early Experience Alters Brain Function and Structure
Heidelise Als;Frank H Duffy;Gloria B McAnulty;Michael J Rivkin.
Pediatrics (2004)
Abnormal Cerebral Structure Is Present at Term in Premature Infants
Terrie E Inder;Simon K Warfield;Hong Wang;Petra Susan Hüppi;Petra Susan Hüppi.
Pediatrics (2005)
Improved watershed transform for medical image segmentation using prior information
V. Grau;A.U.J. Mewes;M. Alcaniz;R. Kikinis.
IEEE Transactions on Medical Imaging (2004)
Quantitative magnetic resonance imaging of brain development in premature and mature newborns
Petra S. Hüppi;Simon Warfield;Ron Kikinis;Patrick D. Barnes.
Annals of Neurology (1998)
Automated Segmentation of MR Images of Brain Tumors
Michael R. Kaus;Simon K. Warfield;Arya Nabavi;Peter M. Black.
Radiology (2001)
Periventricular white matter injury in the premature infant is followed by reduced cerebral cortical gray matter volume at term.
Terrie E. Inder;Petra S. Huppi;Petra S. Huppi;Simon Warfield;Ron Kikinis.
Annals of Neurology (1999)
Serial intraoperative magnetic resonance imaging of brain shift.
Arya Nabavi;Peter McL. Black;David T. Gering;Carl-Fredrik Westin.
Neurosurgery (2001)
Early alteration of structural and functional brain development in premature infants born with intrauterine growth restriction
Cristina Borradori Tolsa;Slava Zimine;Simon K Warfield;Monica Freschi.
Pediatric Research (2004)
Profile was last updated on December 6th, 2021.
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Brigham and Women's Hospital
Brigham and Women's Hospital
Brigham and Women's Hospital
Université Catholique de Louvain
Brigham and Women's Hospital
University of British Columbia
University of Western Australia
University of Geneva
Royal Women's Hospital
Monash University
French Institute for Research in Computer Science and Automation - INRIA
Publications: 76
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