Google AI Blog: Improving Connectomics by an Order of Magnitude

The field of connectomics aims to comprehensively map the structure of the neuronal networks that are found in the nervous system, in order to better understand how the brain works. This process requires imaging brain tissue in 3D at nanometer resolution (typically using electron microscopy), and then analyzing the resulting image data to trace the brain’s neurites and identify individual synaptic connections. Due to the high resolution of the imaging, even a cubic millimeter of brain tissue can generate over 1,000 terabytes of data! In collaboration with researchers from the Max Planck Institute of Neurobiology Google AI designed an RRN that improves the accuracy of automated interpretation of connectomics data by an order of magnitude over previous deep learning techniques.


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