Cargando…
Deep Learning-Based Detection of Malformed Optic Chiasms From MRI Images
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...
Autores principales: | Puzniak, Robert J., Prabhakaran, Gokulraj T., Hoffmann, Michael B. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8573410/ https://www.ncbi.nlm.nih.gov/pubmed/34759795 http://dx.doi.org/10.3389/fnins.2021.755785 |
Ejemplares similares
-
CHIASM-Net: Artificial Intelligence-Based Direct Identification of Chiasmal Abnormalities in Albinism
por: Puzniak, Robert J., et al.
Publicado: (2023) -
Quantifying nerve decussation abnormalities in the optic chiasm
por: Puzniak, Robert J., et al.
Publicado: (2019) -
Cavernous malformation of the optic chiasm: An uncommon location
por: Alafaci, Concetta, et al.
Publicado: (2015) -
CHIASM, the human brain albinism and achiasma MRI dataset
por: Puzniak, Robert J., et al.
Publicado: (2021) -
Cavernous malformation of the optic chiasm: Neuro-endoscopic removal
por: Venkataramana, N. K., et al.
Publicado: (2016)