Abstract
We proposed a generic template-derived approach for (semi-) automated brain extraction in animal MRI studies and evaluated our implementation with different animal models (macaque, marmoset, rodent) and MRI protocols (T1, T2). While conventional MR-neuroimaging studies perform brain extraction as an initial step priming subsequent image-registration from subject to template, our proposed approach propagates an anatomical template to (whole-head) individual subjects in reverse order, which is challenging due to the surrounding extracranial tissue, greater differences in contrast pattern and larger areas with field inhomogeneity. As a novel approach, the herein introduced brain extraction algorithm derives whole-brain segmentation using rigid and non-rigid deformation based on unbiased anatomical atlas building with a priori estimates from study-cohort and an initial approximate brain extraction. We evaluated our proposed method in comparison to several other technical approaches including “Marker based watershed scalper”, “Brain-Extraction-Tool”, “3dSkullStrip”, “Primatologist-Toolbox”, “Rapid Automatic Tissue Segmentation” and “Robust automatic rodent brain extraction using 3D pulse-coupled neural networks” with manual skull-stripping as reference standard. ABX demonstrated best performance with accurate (≥92%) and consistent results throughout datasets and across species, age and MRI protocols. ABX was made available to the public with documentation, templates and sample material (https://www.github.com/jlohmeier/atlasBREX).
Highlights
Brain extraction, referred as skull-stripping or whole-brain segmentation, describes the process of extracting the brain from the surrounding extracranial tissue
While spatial transformation is conventionally performed after image preprocessing with the objective to align images within or across individuals, our proposed approach is based on the backpropagation of an anatomical template to the individual subject, which is challenging due to the surrounding extracranial tissue, greater differences in contrast pattern and larger areas with strong field inhomogeneity
We evaluated our approach with infant and juvenile non-human primates, which can be considered challenging due to differences in brain volume and shape with regard to fixed a priori estimates in most brain extraction algorithms
Summary
Referred as skull-stripping or whole-brain segmentation, describes the process of extracting the brain from the surrounding extracranial tissue. We proposed a generic template-derived approach for animal neuroimaging: We present atlasBREX (ABX), a semi-automated processing pipeline that propagates skull-stripping of an anatomical template built from the study-cohort after rigid and non-rigid deformation to each individual subject (see Fig. 2). While spatial transformation is conventionally performed after image preprocessing (including brain extraction) with the objective to align images within or across individuals, our proposed approach is based on the backpropagation of an anatomical template to the (whole-head) individual subject, which is challenging due to the surrounding extracranial tissue, greater differences in contrast pattern and larger areas with strong field inhomogeneity (see Fig. 1)
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