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Automatic thalamus and hippocampus segmentation from MP2RAGE: comparison of publicly available methods and implications for DTI quantification

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Automatic thalamus and hippocampus segmentation from MP2RAGE: comparison of publicly available methods and implications for DTI quantification

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Naess-Schmidt, E.; Tietze, A.; Blicher, JU.; Petersen, M.; Mikkelsen, IK.; Coupe, P.; Manjón Herrera, JV.... (2016). Automatic thalamus and hippocampus segmentation from MP2RAGE: comparison of publicly available methods and implications for DTI quantification. International Journal of Computer Assisted Radiology and Surgery. 11(11):1979-1991. https://doi.org/10.1007/s11548-016-1433-0

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Título: Automatic thalamus and hippocampus segmentation from MP2RAGE: comparison of publicly available methods and implications for DTI quantification
Autor: Naess-Schmidt, Erhard Tietze, Anna Blicher, Jakob Udby Petersen, Mikkel Mikkelsen, Irene K. Coupe, Pierrick Manjón Herrera, José Vicente Eskildsen, Simon Fristed
Entidad UPV: Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica
Fecha difusión:
Resumen:
Purpose In both structural and functional MRI, there is a need for accurate and reliable automatic segmentation of brain regions. Inconsistent segmentation reduces sensitivity and may bias results in clinical studies. ...[+]
Palabras clave: MRI , Segmentation , Hippocampus , Thalamus , MP2RAGE , Diffusion-weighted imaging
Derechos de uso: Cerrado
Fuente:
International Journal of Computer Assisted Radiology and Surgery. (issn: 1861-6410 )
DOI: 10.1007/s11548-016-1433-0
Editorial:
Springer Verlag (Germany)
Versión del editor: https://link.springer.com/article/10.1007/s11548-016-1433-0
Código del Proyecto:
info:eu-repo/grantAgreement/Ministry of Higher Education and Science//9065250/
info:eu-repo/grantAgreement/ANR//ANR-10-LABX-0057/FR/Translational Research and Advanced Imaging Laboratory/TRAIL/
info:eu-repo/grantAgreement/ANR//ANR-10-IDEX-0003/FR/Initiative d’excellence de l’Université de Bordeaux/IDEX BORDEAUX/
info:eu-repo/grantAgreement/MINECO//TIN2013-43457-R/ES/CARACTERIZACION DE FIRMAS BIOLOGICAS DE GLIOBLASTOMAS MEDIANTE MODELOS NO-SUPERVISADOS DE PREDICCION ESTRUCTURADA BASADOS EN BIOMARCADORES DE IMAGEN/
Agradecimientos:
This work was funded in part by MINDLab UNIK initiative at Aarhus University, funded by the Danish Ministry of Science, Technology and Innovation, Grant Agreement Number 09065250, partly by the Spanish grant TIN2013-43457-R ...[+]
Tipo: Artículo

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