TReMAP: Automatic 3D Neuron Reconstruction Based on Tracing, Reverse Mapping and Assembling of 2D Projections
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Efficient and accurate digital reconstruction of neurons from large-scale 3D microscopic images remains a challenge in neuroscience. We propose a new automatic 3D neuron reconstruction algorithm, TReMAP, which utilizes 3D Virtual Finger (a reverse-mapping technique) to detect 3D neuron structures based on tracing results on 2D projection planes. Our fully automatic tracing strategy achieves close performance with the state-of-the-art neuron tracing algorithms, with the crucial advantage of efficient computation (much less memory consumption and parallel computation) for large-scale images.
KeywordsNeuron reconstruction 2D Projection Reverse mapping Virtual finger Vaa3D
We thank Nuno da Costa, Staci Sorensen, Julie Harris, Raina D’Aleo, and Soumya Chatterjee for providing the images of mouse neurons, Paloma Gonzalez-Bellido for providing the images of dragonfly neurons, Hanbo Chen and Yujie Li for comments. This work is supported by the Allen Institute for Brain Science.
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