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Myelin Sheath

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Deep learning-based segmentation in MRI-(immuno)histological examination of myelin and axonal damage in normal-appearing white matter and white matter hyperintensities.

Brain pathology (Zurich, Switzerland)
The major vascular cause of dementia is cerebral small vessel disease (SVD). Its diagnosis relies on imaging hallmarks, such as white matter hyperintensities (WMH). WMH present a heterogenous pathology, including myelin and axonal loss. Yet, these mi...

A multi-spectral myelin annotation tool for machine learning based myelin quantification.

F1000Research
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-...

Interpretable deep learning of myelin histopathology in age-related cognitive impairment.

Acta neuropathologica communications
Age-related cognitive impairment is multifactorial, with numerous underlying and frequently co-morbid pathological correlates. Amyloid beta (Aβ) plays a major role in Alzheimer's type age-related cognitive impairment, in addition to other etiopatholo...

Automated stain-free histomorphometry of peripheral nerve by contrast-enhancing techniques and artificial intelligence.

Journal of neuroscience methods
BACKGROUND: Traditional histopathologic evaluation of peripheral nerve using brightfield microscopy is resource-intensive, necessitating complex sample preparation. Label-free imaging techniques paired with artificial intelligence-based image reconst...

Rapid, automated nerve histomorphometry through open-source artificial intelligence.

Scientific reports
We aimed to develop and validate a deep learning model for automated segmentation and histomorphometry of myelinated peripheral nerve fibers from light microscopic images. A convolutional neural network integrated in the AxonDeepSeg framework was tra...

Overview of quantitative susceptibility mapping using deep learning: Current status, challenges and opportunities.

NMR in biomedicine
Quantitative susceptibility mapping (QSM) has gained broad interest in the field by extracting bulk tissue magnetic susceptibility, predominantly determined by myelin, iron and calcium from magnetic resonance imaging (MRI) phase measurements in vivo....

Estimating myelin-water content from anatomical and diffusion images using spatially undersampled myelin-water imaging through machine learning.

NeuroImage
Myelin is vital for healthy neuronal development, and can therefore provide valuable information regarding neuronal maturation. Anatomical and diffusion weighted images (DWI) possess information related to the myelin content and the current study inv...

Myelin detection in fluorescence microscopy images using machine learning.

Journal of neuroscience methods
BACKGROUND: The myelin sheath produced by glial cells insulates the axons, and supports the function of the nervous system. Myelin sheath degeneration causes neurodegenerative disorders, such as multiple sclerosis (MS). There are no therapies for MS ...

Myelin water imaging data analysis in less than one minute.

NeuroImage
PURPOSE: Based on a deep learning neural network (NN) algorithm, a super fast and easy to implement data analysis method was proposed for myelin water imaging (MWI) to calculate the myelin water fraction (MWF).

Measurement-oriented deep-learning workflow for improved segmentation of myelin and axons in high-resolution images of human cerebral white matter.

Journal of neuroscience methods
BACKGROUND: Standard segmentation of high-contrast electron micrographs (EM) identifies myelin accurately but does not translate easily into measurements of individual axons and their myelin, even in cross-sections of parallel fibers. We describe aut...