Deep Learning-Based Detection of Malformed Optic Chiasms From MRI Images.
CNN
albinism
chiasmal malformations
convolutional neural network
misrouting detection
nerve misrouting
optic chiasm
Journal
Frontiers in neuroscience
ISSN: 1662-4548
Titre abrégé: Front Neurosci
Pays: Switzerland
ID NLM: 101478481
Informations de publication
Date de publication:
2021
2021
Historique:
received:
09
08
2021
accepted:
16
09
2021
entrez:
11
11
2021
pubmed:
12
11
2021
medline:
12
11
2021
Statut:
epublish
Résumé
Convolutional neural network (CNN) models are of great promise to aid the segmentation and analysis of brain structures. Here, we tested whether CNN trained to segment normal optic chiasms from the T1w magnetic resonance imaging (MRI) image can be also applied to abnormal chiasms, specifically with optic nerve misrouting as typical for human albinism. We performed supervised training of the CNN on the T1w images of control participants (
Identifiants
pubmed: 34759795
doi: 10.3389/fnins.2021.755785
pmc: PMC8573410
doi:
Types de publication
Journal Article
Langues
eng
Pagination
755785Informations de copyright
Copyright © 2021 Puzniak, Prabhakaran and Hoffmann.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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