1. A multi-spectral myelin annotation tool for machine learning based myelin quantification [version 4; peer review: 2 approved]
- Author
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Abdulkerim Çapar, Dursun Ali Ekinci, Umut Engin Ayten, Sibel Çimen, Zeynep Aladağ, Behçet Uğur Töreyin, and Bilal Ersen Kerman
- Subjects
myelin annotation tool ,myelin quantification ,fluorescence images ,machine learning ,image analysis ,eng ,Medicine ,Science - Abstract
Myelin is an essential component of the nervous system and myelin damage causes demyelination diseases. Myelin is a sheet of oligodendrocyte membrane wrapped around the neuronal axon. In the fluorescent images, experts manually identify myelin by co-localization of oligodendrocyte and axonal membranes that fit certain shape and size criteria. Because myelin wriggles along x-y-z axes, machine learning is ideal for its segmentation. However, machine-learning methods, especially convolutional neural networks (CNNs), require a high number of annotated images, which necessitate expert labor. To facilitate myelin annotation, we developed a workflow and software for myelin ground truth extraction from multi-spectral fluorescent images. Additionally, to the best of our knowledge, for the first time, a set of annotated myelin ground truths for machine learning applications were shared with the community.
- Published
- 2023
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