Mr. Arthur Le Maout Profile

Arthur Le Maout

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Proceedings Article | 28 February 2020 Presentation + Paper

Automatic measurement of extra-axial CSF from infant MRI data

Arthur LeMaout, Han Bit Yoon, Sun Hyung Kim, Mahmoud Mostapha, Mark Shen, Juan Prieto, Martin Styner

Proceedings Volume 11317, 113171I (2020) https://doi.org/10.1117/12.2550006

KEYWORDS: Brain, Neuroimaging, Magnetic resonance imaging, Image segmentation, Skull, Tissues, Human-machine interfaces, Brain mapping, Image registration, Data conversion

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The quantification of cerebrospinal fluid (CSF) in the human brain has shown to play an important role in early postnatal brain development. Extra-axial fluid (EA-CSF), which is characterized by CSF in the subarachnoid space, is a promising marker for the early detection of children at risk for neurodevelopmental disorders, such as Autism Spectrum Disorder (ASD). Yet, non-ventricular CSF quantification, in particular extra-axial CSF quantification, is not supported in the major neuro-imaging software solutions, such as FreeSurfer. Most current structural image analysis packages mask out the extra-axial CSF space in one of the first pre-processing steps. A quantitative protocol was previously developed by our group to objectively measure the volume of total EA-CSF volume using a pipeline workflow implemented in a series of python scripts. While this solution worked for our specific lab, a graphical user interface-based tool is necessary to facilitate the computation of extra-axial CSF volume across a wide array of neuroimaging studies and research labs. This paper presents the development of a novel open-source, cross-platform, user-friendly software tool, called Auto-EACSF, for the automatic computation of such extra-axial CSF volume. Auto-EACSF allows neuroimaging labs to quantify extra-axial CSF in their neuroimaging studies in order to investigate its role in normal and atypical brain development.

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