A FreeSurfer-compliant consistent manual segmentation of infant brains spanning the 0-2 year age range

Katyucia de Macedo Rodrigues; Emma Ben-Avi; Danielle D Sliva; Myong-Sun Choe; Marie Drottar; Ruopeng Wang; Bruce Fischl; Patricia E Grant; Lilla Zöllei

doi:10.3389/fnhum.2015.00021

A FreeSurfer-compliant consistent manual segmentation of infant brains spanning the 0-2 year age range

Front Hum Neurosci. 2015 Feb 18:9:21. doi: 10.3389/fnhum.2015.00021. eCollection 2015.

Authors

Katyucia de Macedo Rodrigues¹, Emma Ben-Avi², Danielle D Sliva³, Myong-Sun Choe¹, Marie Drottar¹, Ruopeng Wang², Bruce Fischl⁴, Patricia E Grant¹, Lilla Zöllei²

Affiliations

¹ Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital Boston, MA, USA.
² Laboratory of Computational Neuroimaging, AA Martinos Center, Massachusetts General Hospital Charlestown, MA, USA.
³ 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.
⁴ 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.

Abstract

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.

Keywords: MRI imaging; atlas; neuroimaging; pediatrics; segmentation.

Abstract

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