Journal article

Software Pipeline for Midsagittal Corpus Callosum Thickness Profile Processing

Chris Adamson, Richard Beare, Mark Walterfang, Marc Seal

Neuroinformatics | HUMANA PRESS INC | Published : 2014

Abstract

This paper presents a fully automated pipeline for thickness profile evaluation and analysis of the human corpus callosum (CC) in 3D structural T 1-weighted magnetic resonance images. The pipeline performs the following sequence of steps: midsagittal plane extraction, CC segmentation algorithm, quality control tool, thickness profile generation, statistical analysis and results figure generator. The CC segmentation algorithm is a novel technique that is based on a template-based initialisation with refinement using mathematical morphology operations. The algorithm is demonstrated to have high segmentation accuracy when compared to manual segmentations on two large, publicly available dataset..

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Funding Acknowledgements

This research was conducted within the Developmental Imaging research group, Murdoch Childrens Research Institute at the Children's MRI Centre, Royal Children's Hospital, Melbourne Victoria. It was supported by the Murdoch Childrens Research Institute, Royal Children's Hospital, The University of Melbourne Department of Paediatrics and the Victorian Government's Operational Infrastructure Support Program.