Myelin Segmentation in Fluorescence Microscopy Images

Cimen, Sibel; Ekinci, Dursun Ali; Cakir, Ertan; Ekşioğlu, Ender M.; Ayten, Umut Engin; Çapar, Abdulkerim; Töreyi̇n, Behçet Uğur; Kerman, Bilal E.

doi:10.1109/tiptekno.2019.8895041

Cited by 5 publications

(3 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is not possible for patients to fully recover from CNS damage causing different neurodegenerative diseases such as Alzheimer's, Parkinson's, Huntington's Diseases, multiple sclerosis (MS), and epilepsy with currently available treatments [1,2]. For this reason, there is a need for new-generation studies in the field of neural tissue engineering [1,[3][4][5]. The central nervous system (CNS) comprises the brain and the spinal cord, and the majority of neural tissue in the central nervous system comprises two cell types, neuronal cells, and glial cells.…”

Section: Introductionmentioning

confidence: 99%

Comparision of the Glio-Protective Effects of Biopolymer Coated Electrospun Scaffolds

BATTALOĞLU,

MORÇİMEN,

ŞENDEMİR

2023

Hacettepe Journal of Biology and Chemistry

View full text Add to dashboard Cite

Gliosis is a condition that plays a negative role in various neurological pathologies. In this study, it was aimed to obtain and compare the glio-protective effects of electrospun fibrous scaffolds coated by different biopolymers. First, in vitro gliosis model was obtained by inducing U-87 MG cells with LPS and IFN-γ. The optimized model was applied to U-87 MG cells grown on polycaprolactone (PCL), hyaluronic acid (HA) coated, gelatin coated, and collagen coated PCL scaffolds. Immunofluorescent (IF) staining was performed with glial fibrillary acidic protein (GFAP) antibody to determine the level of gliosis. It was found that 5µg/mL LPS concentration induced gliosis and hyaluronic acid-coated PCL scaffolds have shown a protective effect on gliosis.

show abstract

Section: Introductionmentioning

confidence: 99%

Comparision of the Glio-Protective Effects of Biopolymer Coated Electrospun Scaffolds

BATTALOĞLU,

MORÇİMEN,

ŞENDEMİR

2023

Hacettepe Journal of Biology and Chemistry

View full text Add to dashboard Cite

show abstract

“…The entire process, which would have taken several weeks, took approximately 5 days. More than 30,000 feature images were extracted from these five images and were used for testing various machine-learning methods [8][9][10] . The annotated images, which are available with the manuscript, are a resource for the researchers working not only on myelin detection but also on segmenting multi-spectral images.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

View full text Add to dashboard Cite

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.

show abstract

“…The entire process, which would have taken several weeks, took approximately 5 days. More than 30,000 feature images were extracted from these five images and were used for testing various machine-learning methods [7][8][9] . The annotated images, which are available with the manuscript, are a resource for the researchers working not only on myelin detection but also on segmenting multi-spectral images.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

View full text Add to dashboard Cite

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 necessitates expert labor. To facilitate myelin annotation, we developed a workflow and a software for myelin ground truth extraction from multi-spectral fluorescent images. Additionally, we shared a set of myelin ground truths annotated using this workflow.

show abstract

Myelin Segmentation in Fluorescence Microscopy Images

Cited by 5 publications

References 9 publications

Comparision of the Glio-Protective Effects of Biopolymer Coated Electrospun Scaffolds

Comparision of the Glio-Protective Effects of Biopolymer Coated Electrospun Scaffolds

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

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

Contact Info

Product

Resources

About