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BonsaiNet

License

Goal

The intricate morphology of neurons has fascinated scientists since the dawn of neuroscience. Here we use recent techniques of deep learning to build a generative model for 3-d neural structures.This generative model can be used in the simulation of realistic neural structures and in the inference of neuronal structure from imaging techniques.

Approach

Neuronal structures can be approximated as trees in 3-d space. Each neuron is uniquely specified by the adjacency matrix of its tree (morphology) and the location of the tree's vertices in 3-d space. We train generative adversarial networks (GANs) to synthesize the the morphology and geometry of realistic neurons, whose joint statistics are obtained from a neuroanatomy database: neuromorpho.org.

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Prerequisites

installation

Clone the repository.

$ git clone https://github.com/tree-gan/BonsaiNet

bonsainet's Projects

actual-tree icon actual-tree

Even Ramon Cajal compared neurons to the actual trees! so do we!

mcneuron icon mcneuron

Plot, edit, generate and analysis neuron morphologies! and a lot more...

tree-gan icon tree-gan

Generative Adversarial Network for Tree Structured Data

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