English

Isointense infant brain MRI segmentation with a dilated convolutional neural network

Computer Vision and Pattern Recognition 2017-08-10 v1

Abstract

Quantitative analysis of brain MRI at the age of 6 months is difficult because of the limited contrast between white matter and gray matter. In this study, we use a dilated triplanar convolutional neural network in combination with a non-dilated 3D convolutional neural network for the segmentation of white matter, gray matter and cerebrospinal fluid in infant brain MR images, as provided by the MICCAI grand challenge on 6-month infant brain MRI segmentation.

Cite

@article{arxiv.1708.02757,
  title  = {Isointense infant brain MRI segmentation with a dilated convolutional neural network},
  author = {Pim Moeskops and Josien P. W. Pluim},
  journal= {arXiv preprint arXiv:1708.02757},
  year   = {2017}
}

Comments

MICCAI grand challenge on 6-month infant brain MRI segmentation

R2 v1 2026-06-22T21:10:15.106Z