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2017 GTC San Jose

S7449 - Driving the Assembly of the Zebrafish Connectome through Deep Learning

Session Speakers
Session Description

Tracing pathways through large volumes of data is an incredibly tedious, time-consuming process that significantly encumbers progress in neuroscience and the tracing of neurons through an organism. We'll explore the potential for applying deep learning to the automation of high-resolution scanning electron microscope image data segmentation. We've started with neural pathway tracing through 5.1GB of whole-brain serial-section slices from larval zebrafish collected by the Center for Brain Science at Harvard. This kind of manual image segmentation requires years of careful work to properly trace the neural pathways in an organism as small as a zebrafish larvae, which is approximately 5mm in total body length. Automating this process could vastly improve productivity, which would lead to faster data analysis and more breakthroughs in understanding the complexity of the brain.


Additional Session Information
All
Talk
Deep Learning and AI HPC and Supercomputing
Healthcare & Life Sciences
50 minutes
Session Schedule