iBEAT Yes University of North Carolina - Chapel Hill NITRC iBEAT Yes Li Wang 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 2020-1-01 iBEAT V2.0 Cloud 2018-5-05 UNC Neonate and Infant Cortical Surface Atlases 2017-10-02 UNC 4D Infant Cortical Surface Atlas iBEAT Atlas Data, Atlas Application, Segmentation, Registration, Warping, Image Display, Dyslexia, Autistic Disorder, Diabetes Mellitus, Hypertension, Alzheimer Disease, Amyotrophic Lateral Sclerosis, Lymphoma, Non-Hodgkin, Parkinson Disease, MR, iBEAT http://www.nitrc.org/projects/ibeat/, http://http://www.ibeat.cloud/ li_wang@med.unc.edu