Cargando…
101 Labeled Brain Images and a Consistent Human Cortical Labeling Protocol
We introduce the Mindboggle-101 dataset, the largest and most complete set of free, publicly accessible, manually labeled human brain images. To manually label the macroscopic anatomy in magnetic resonance images of 101 healthy participants, we created a new cortical labeling protocol that relies on...
Autores principales: | Klein, Arno, Tourville, Jason |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3514540/ https://www.ncbi.nlm.nih.gov/pubmed/23227001 http://dx.doi.org/10.3389/fnins.2012.00171 |
Ejemplares similares
-
Mindboggle: Automated brain labeling with multiple atlases
por: Klein, Arno, et al.
Publicado: (2005) -
Learning from pseudo-labels: deep networks improve consistency in longitudinal brain volume estimation
por: Zhan, Geng, et al.
Publicado: (2023) -
Limitations of Sulforhodamine 101 for Brain Imaging
por: Hülsmann, Swen, et al.
Publicado: (2017) -
Censoring Distances Based on Labeled Cortical Distance Maps in Cortical Morphometry
por: Ceyhan, Elvan, et al.
Publicado: (2013) -
Dual consistent pseudo label generation for multi-source domain adaptation without source data for medical image segmentation
por: Cai, Binke, et al.
Publicado: (2023)