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Large-scale neuroanatomical visualization using a manifold embedding approach
2010
2010 IEEE Symposium on Visual Analytics Science and Technology
We present a unified framework for data processing, mining and interactive visualization of largescale neuroanatomical databases. The input data is assumed to lie in a specific atlas space, or simply exist as a separate collection. Users can specify their own atlas for comparative analyses. The original data exist as MRI images in standard formats. It is uploaded to a remote server and processed offline by a parallelized pipeline workflow. This workflow transforms the data to represent it as
doi:10.1109/vast.2010.5652532
pmid:21318096
pmcid:PMC3037590
dblp:conf/ieeevast/JoshiBH10
fatcat:4m2fc7lfrnbdnbwkezjwilyviu