iBEAT: Infant Brain Extraction and Analysis Toolbox. Since 2008, PIs in UNC-Chapel Hill have been working on developing infant-dedicated computational tools. In 2012, the iBEAT toolbox was released for infant brain MRI processing, which is more challenging due to the low tissue contrast in comparison with the adult MRI. So far, it has been validated on thousands of infant subjects.

News: iBEAT V2.0 Cloud is now available online (http://www.ibeat.cloud/). Users can process any age of pediatric images via uploading images into iBEAT Cloud. The current main functionality includes skull stripping, tissue segmentation, surface reconstruction, surface measurement, and surface parcellation. Up to date, iBEAT V2.0 Cloud has successfully processed 5200+ infant brain images from 70+ institutions. Please check user feedback: https://ibeat.wildapricot.org/Feedbacks
and demos on images from BCP and dHCP, comparison with infant freesurfer, and results on images with severe artifacts: https://ibeat.wildapricot.org/Demos

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Other Keywords:
deep learning