TL;DR
AxonDeepSeg is an open-source deep learning tool that accurately segments axons and myelin in microscopy images, facilitating quantitative analysis of nervous tissue microstructure across species.
Contribution
It introduces a convolutional neural network-based method with ready-to-use models for axon and myelin segmentation, simplifying the process and reducing user parameter tuning.
Findings
High pixel-wise accuracy across species and microscopy modalities
Effective segmentation of full spinal cord slices
Open-source availability for broad research use
Abstract
Segmentation of axon and myelin from microscopy images of the nervous system provides useful quantitative information about the tissue microstructure, such as axon density and myelin thickness. This could be used for instance to document cell morphometry across species, or to validate novel non-invasive quantitative magnetic resonance imaging techniques. Most currently-available segmentation algorithms are based on standard image processing and usually require multiple processing steps and/or parameter tuning by the user to adapt to different modalities. Moreover, only few methods are publicly available. We introduce AxonDeepSeg, an open-source software that performs axon and myelin segmentation of microscopic images using deep learning. AxonDeepSeg features: (i) a convolutional neural network architecture; (ii) an easy training procedure to generate new models based on…
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