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Front Neuroinform. 2016 Aug 19;10:37. doi: 10.3389/fninf.2016.00037. eCollection 2016.

AxonSeg: Open Source Software for Axon and Myelin Segmentation and Morphometric Analysis.

Author information

1
Institute of Biomedical Engineering, Polytechnique Montreal Montreal, QC, Canada.
2
Institut Universitaire en Santé Mentale de QuébecQuebec, QC, Canada; Centre d'Optique, Photonique et Laser, Université LavalQuebec, QC, Canada.
3
Institute of Biomedical Engineering, Polytechnique MontrealMontreal, QC, Canada; Montreal Heart InstituteMontreal, QC, Canada.
4
Institute of Biomedical Engineering, Polytechnique MontrealMontreal, QC, Canada; Functional Neuroimaging Unit, CRIUGM, Université de MontréalMontreal, QC, Canada.

Abstract

Segmenting axon and myelin from microscopic images is relevant for studying the peripheral and central nervous system and for validating new MRI techniques that aim at quantifying tissue microstructure. While several software packages have been proposed, their interface is sometimes limited and/or they are designed to work with a specific modality (e.g., scanning electron microscopy (SEM) only). Here we introduce AxonSeg, which allows to perform automatic axon and myelin segmentation on histology images, and to extract relevant morphometric information, such as axon diameter distribution, axon density and the myelin g-ratio. AxonSeg includes a simple and intuitive MATLAB-based graphical user interface (GUI) and can easily be adapted to a variety of imaging modalities. The main steps of AxonSeg consist of: (i) image pre-processing; (ii) pre-segmentation of axons over a cropped image and discriminant analysis (DA) to select the best parameters based on axon shape and intensity information; (iii) automatic axon and myelin segmentation over the full image; and (iv) atlas-based statistics to extract morphometric information. Segmentation results from standard optical microscopy (OM), SEM and coherent anti-Stokes Raman scattering (CARS) microscopy are presented, along with validation against manual segmentations. Being fully-automatic after a quick manual intervention on a cropped image, we believe AxonSeg will be useful to researchers interested in large throughput histology. AxonSeg is open source and freely available at: https://github.com/neuropoly/axonseg.

KEYWORDS:

axon; discriminant analysis; g-ratio; graphical user interface; histology; microscopy; myelin; segmentation

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