2023 - Research.com Computer Science in Canada Leader Award
D. Louis Collins spends much of his time researching Artificial intelligence, Magnetic resonance imaging, Computer vision, Segmentation and Pattern recognition. His work carried out in the field of Artificial intelligence brings together such families of science as Transformation and Atlas. His biological study spans a wide range of topics, including Nuclear medicine, Pathology, Neuroimaging, Neuroscience and Temporal lobe.
The concepts of his Computer vision study are interwoven with issues in Imaging phantom and Affine transformation. His Segmentation study combines topics from a wide range of disciplines, such as Hippocampus and Identification. His Pattern recognition study integrates concerns from other disciplines, such as Spatial normalization, Voxel, Brain mapping and Contrast.
His primary scientific interests are in Artificial intelligence, Pattern recognition, Magnetic resonance imaging, Computer vision and Segmentation. Many of his studies involve connections with topics such as Imaging phantom and Artificial intelligence. His research integrates issues of Hyperintensity and Atlas in his study of Pattern recognition.
His Magnetic resonance imaging study incorporates themes from Nuclear medicine, Pathology, Neuroimaging, Neuroscience and Multiple sclerosis. In his research, Grey matter is intimately related to Atrophy, which falls under the overarching field of Neuroscience. His Segmentation study focuses on Scale-space segmentation in particular.
His scientific interests lie mostly in Cognition, Internal medicine, Hyperintensity, Disease and Neuroimaging. The various areas that D. Louis Collins examines in his Cognition study include Audiology, Cohort and Cognitive decline. D. Louis Collins has researched Hyperintensity in several fields, including White matter, Irritability and Kappa.
His studies in Neuroimaging integrate themes in fields like Cartography, Insula and Magnetic resonance imaging. The concepts of his Magnetic resonance imaging study are interwoven with issues in Segmentation, Artificial intelligence, Pattern recognition, Imaging phantom and Atlas. His Artificial intelligence study frequently links to other fields, such as Positron emission tomography.
His scientific interests lie mostly in Cognition, Disease, Internal medicine, Cohort and Neuroimaging. D. Louis Collins combines subjects such as Brain development and Dementia, Cognitive decline with his study of Cognition. His Neuroimaging research is multidisciplinary, incorporating elements of Prefrontal cortex, Magnetic resonance imaging, Human Connectome Project, Voxel and Waist.
D. Louis Collins interconnects Imaging phantom and Resting state fMRI in the investigation of issues within Magnetic resonance imaging. His Hyperintensity research includes themes of Segmentation, Test set, Artificial intelligence, Pattern recognition and Ranking. His Artificial intelligence research incorporates themes from Diagnostic biomarker and Atlas.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)
Bjoern H. Menze;Andras Jakab;Stefan Bauer;Jayashree Kalpathy-Cramer.
IEEE Transactions on Medical Imaging (2015)
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.
Design and construction of a realistic digital brain phantom
D.L. Collins;A.P. Zijdenbos;V. Kollokian;J.G. Sled.
IEEE Transactions on Medical Imaging (1998)
Structural Maturation of Neural Pathways in Children and Adolescents: In Vivo Study
Tomáš Paus;Alex Zijdenbos;Keith Worsley;D. Louis Collins.
Unbiased Average Age-Appropriate Atlases for Pediatric Studies
Vladimir S. Fonov;Alan C. Evans;Kelly N. Botteron;C. Robert Almli.
Enhancement of MR images using registration for signal averaging
Colin J. Holmes;Rick Hoge;Louis Collins;Roger Woods.
Journal of Computer Assisted Tomography (1998)
Automatic 3-D model-based neuroanatomical segmentation
D. Louis Collins;C. J. Holmes;T. M. Peters;A. C. Evans.
Human Brain Mapping (1995)
Adaptive non‐local means denoising of MR images with spatially varying noise levels
José V. Manjón;Pierrick Coupé;Luis Martí-Bonmatí;D. Louis Collins.
Journal of Magnetic Resonance Imaging (2010)
Early brain development in infants at high risk for autism spectrum disorder
Heather Cody Hazlett;Hongbin Gu;Brent C. Munsell;Sun Hyung Kim.
Patch-based segmentation using expert priors: application to hippocampus and ventricle segmentation.
Pierrick Coupé;José V. Manjón;Vladimir S. Fonov;Jens C. Pruessner.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: