Online infant processing pipeline: iBEAT V2.0 Cloud
- iBEAT V2.0 Cloud, http://www.ibeat.cloud/. iBEAT V2.0 Cloud is a toolbox for processing infant brain MR images, using multimodality (including T1w and T2w) or single-modality. Main functions of the software (step by step) include image preprocessing, brain extraction, tissue segmentation and brain labeling. The software is developed by the IDEA group at the University of North Carolina at Chapel Hill. iBEAT was first developed in 2012, now re-developed with more advanced techniques. So far, we have successfully processed 8200+ infant brain images from multiple sites with various protocols and scanners (Table 1).
Table 1. Successfully processed 8200+ infant brain images from multiple sites with various protocols and scanners.
- Volume-based Analysis of 6-month-old Infant Brain MRI for Autism BioMarker Identification and Early Diagnosis [PDF] [Code: Caffe prototxt] [Software]
- LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images. This novel method employs the random forest and auto-context model. [Journal version] [PPT] [Email request for the code]
- Neonatal Brain MR Image Segmentation using Sparse Representation and Patch-Driven Level Sets, Neuroimage, 84, 141-158, 2014. [PDF] [PPT][Matlab code]
- Longitudinally guided level sets for consistent tissue segmentation of neonates, Human Brain Mapping, 34(4), 956-972, 2013.[PDF][BibTex][Infant processing software].
- Automatic Segmentation of Neonatal Images Using Convex Optimization and Coupled Level Sets, NeuroImage, 58:805-817, 2011. [PDF][Infant processing software]
- Medical Image Segmentation with Local Gaussian Distribution (LGD) Fitting Energy [PDF][Matlab Source Code]
- One zip file with training/testing images and manual labels is available for download. The zip file contains T1- and T2-weighted MR images of 39 infant subjects from multiple sites (the challenge is always open):
- One zip file with training images and manual labels is available for download. The zip file contains T1- and T2-weighted MR images of 10 infant subjects (the challenge is always open):