Segmentation of neonatal brain MR images using patch-driven level sets
Year: 2013
Type: article
Source: NeuroImage
Institutions: University of North Carolina at Chapel Hill, Korea University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funders: National Institutes of Health, National Institute on Aging, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Institute of Biomedical Imaging and Bioengineering, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Awards: G1234639804, G1529334509, Early Brain Development in Twins, G2211031860, G229738346, G2391590095, G2431482247, G2686953907, G2849260730, G3186634833, G3258782064, Prospective Studies of the Pathogenesis of Schizophrenia, Assessing Large-scale Brain Connectivities in Mild Cognitive Impairment, G4798393751, G4847335975, Quantifying Brain Abnormality by Multimodality Neuroimage Analysis, G6575006414, G665197000, Development of Robust Brain Measurement Tools Informed by Ultrahigh Field 7T MRI, Characterization of Normal Brain Development Using Parallel MRI, G7662282662, G8341723830, G9000040056, G9000081443, G9000104217, G9000108347, G9000147613, G9000184678, G9000307525
OpenAlex ID: W2059911466