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Journal of Undergraduate Research

Keywords

landmark vs manual tracing, hippocampal segmentation, diseased populations

College

Family, Home, and Social Sciences

Department

Psychology

Abstract

Calculating hippocampal volume from MR images is an essential task in many studies of neurocognition in healthy and diseased populations. The “gold standard” method involves hand tracing, which is accurate but laborious, requiring expertly trained researchers and significant amounts of time. As such, segmenting large datasets with the standard method is impractical. Current automated pipelines are inaccurate at hippocampal demarcation and volumetry. We developed a semi-automated hippocampal segmentation pipeline based on the Advanced Normalization Tools (ANTs) suite of programs to segment the hippocampus. We applied the semi-automated segmentation pipeline to 172 scans (59 female) from groups that included participants diagnosed with autism spectrum disorder, healthy older adults (mean age 67) and healthy younger controls. We found that pipeline performed best when including manually-placed landmarks and when using a template generated from a heterogeneous sample (that included the full variability of group assignments) than a template generated from more homogeneous samples (using only individuals within a given age or neuropsychiatric diagnosis group). Additionally, the semi-automated pipeline required much less time (5 minutes per brain) than manual segmentation (30-60 minutes per brain).

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