Journal
FRONTIERS IN NEUROINFORMATICS
Volume 13, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fninf.2019.00061
Keywords
CT; image processing; image normalization; image analysis; non-contrast CT; image de-identification; neuroimaging; neuroimaging analysis
Funding
- National Institute of Neurological Disorders and Stroke at the National Institutes of Health (NINDS/NIH) [R01NS060910, 5U01NS080824]
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Many research applications of neuroimaging use magnetic resonance imaging (MRI). As such, recommendations for image analysis and standardized imaging pipelines exist. Clinical imaging, however, relies heavily on X-ray computed tomography (CT) scans for diagnosis and prognosis. Currently, there is only one image processing pipeline for head CT, which focuses mainly on head CT data with lesions. We present tools and a complete pipeline for processing CT data, focusing on open-source solutions, that focus on head CT but are applicable to most CT analyses. We describe going from raw DICOM data to a spatially normalized brain within CT presenting a full example with code. Overall, we recommend anonymizing data with Clinical Trials Processor, converting DICOM data to NIfTI using dcm2niix, using BET for brain extraction, and registration using a publicly-available CT template for analysis.
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