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A FreeSurfer-compliant consistent manual segmentation of infant brains spanning the 0-2 year age range.
de Macedo Rodrigues, Katyucia; Ben-Avi, Emma; Sliva, Danielle D; Choe, Myong-Sun; Drottar, Marie; Wang, Ruopeng; Fischl, Bruce; Grant, Patricia E; Zöllei, Lilla.
Afiliación
  • de Macedo Rodrigues K; Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital Boston, MA, USA.
  • Ben-Avi E; Laboratory of Computational Neuroimaging, AA Martinos Center, Massachusetts General Hospital Charlestown, MA, USA.
  • Sliva DD; Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital Boston, MA, USA ; Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital Boston, MA, USA.
  • Choe MS; Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital Boston, MA, USA.
  • Drottar M; Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital Boston, MA, USA.
  • Wang R; Laboratory of Computational Neuroimaging, AA Martinos Center, Massachusetts General Hospital Charlestown, MA, USA.
  • Fischl B; Laboratory of Computational Neuroimaging, AA Martinos Center, Massachusetts General Hospital Charlestown, MA, USA ; Department of Electrical Engineering and Computer Science, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology Cambridge, MA, USA.
  • Grant PE; Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital Boston, MA, USA.
  • Zöllei L; Laboratory of Computational Neuroimaging, AA Martinos Center, Massachusetts General Hospital Charlestown, MA, USA.
Front Hum Neurosci ; 9: 21, 2015.
Article en En | MEDLINE | ID: mdl-25741260
We present a detailed description of a set of FreeSurfer compatible segmentation guidelines tailored to infant MRI scans, and a unique data set of manually segmented acquisitions, with subjects nearly evenly distributed between 0 and 2 years of age. We believe that these segmentation guidelines and this dataset will have a wide range of potential uses in medicine and neuroscience.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Hum Neurosci Año: 2015 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Hum Neurosci Año: 2015 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza