Bundle geodesic convolutional neural network for diffusion-weighted imaging segmentation

PURPOSE: Applying machine learning techniques to magnetic resonance diffusion-weighted imaging (DWI) data is challenging due to the size of individual data samples and the lack of labeled data. It is possible, though, to learn general patterns from a very limited amount of training data if we take a...

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Detalles Bibliográficos
Autores principales: Liu, Renfei, Lauze, François, Erleben, Kenny, Berg, Rune W., Darkner, Sune
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Photo-Optical Instrumentation Engineers 2022
Materias:
Image Processing
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9670506/
https://www.ncbi.nlm.nih.gov/pubmed/36405814
http://dx.doi.org/10.1117/1.JMI.9.6.064002

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9670506/
https://www.ncbi.nlm.nih.gov/pubmed/36405814
http://dx.doi.org/10.1117/1.JMI.9.6.064002

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