Work

Automatic segmentation of neonatal images using convex optimization and coupled level sets

Year: 2011

Type: article

Source: NeuroImage

DOI: 10.1016/j.neuroimage.2011.06.064

Authors: Li Wang, Feng Shi, Weili Lin, John H. Gilmore, Dinggang Shen

Institution: University of North Carolina at Chapel Hill

Language: English

Topic: Medical Image Segmentation Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, 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: G1529334509, G1761222865, Early Brain Development in One and Two Year Olds, G2211031860, G2686953907, G2849260730, G3258782064, Prospective Studies of the Pathogenesis of Schizophrenia, Continued Development of HAMMER Algorithm for Fast Registration, G4798393751, G5294563186, G665197000, Development of Robust Brain Measurement Tools Informed by Ultrahigh Field 7T MRI, Characterization of Normal Brain Development Using Parallel MRI, G7662282662, G8341723830

OpenAlex ID: W2168031320

FWCI: 12.39

Cites: 47

Cited by: 130

Related to: 10