Comparing 3D, 2.5D, and 2D Approaches to Brain Image Auto-Segmentation

Deep-learning methods for auto-segmenting brain images either segment one slice of the image (2D), five consecutive slices of the image (2.5D), or an entire volume of the image (3D). Whether one approach is superior for auto-segmenting brain images is not known. We compared these three approaches (3...

Descripción completa

Detalles Bibliográficos
Autores principales: Avesta, Arman, Hossain, Sajid, Lin, MingDe, Aboian, Mariam, Krumholz, Harlan M., Aneja, Sanjay
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9952534/
https://www.ncbi.nlm.nih.gov/pubmed/36829675
http://dx.doi.org/10.3390/bioengineering10020181

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9952534/
https://www.ncbi.nlm.nih.gov/pubmed/36829675
http://dx.doi.org/10.3390/bioengineering10020181

Ejemplares similares