Infant Brain Mri Segmentation
4 papers with code • 1 benchmarks • 0 datasets
Most implemented papers
3D Densely Convolutional Networks for Volumetric Segmentation
The proposed network architecture provides a dense connection between layers that aims to improve the information flow in the network.
3D Densely Convolutional Networks for VolumetricSegmentation
The proposed network architecture provides a dense connection between layers that aims to improve the information flow in the network.
Isointense Infant Brain Segmentation with a Hyper-dense Connected Convolutional Neural Network
Neonatal brain segmentation in magnetic resonance (MR) is a challenging problem due to poor image quality and low contrast between white and gray matter regions.
Deep CNN ensembles and suggestive annotations for infant brain MRI segmentation
We report evaluations of our method on the public data of the MICCAI iSEG-2017 Challenge on 6-month infant brain MRI segmentation, and show very competitive results among 21 teams, ranking first or second in most metrics.