Difference between revisions of "Publications/xu.17.icip.inc"

From LRDE

(Datasets)
(Experiments)
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== Illustrations ==
 
== Illustrations ==
 
=== Experiments ===
 
=== Experiments ===
  +
Leave-One-Subject-Out (LOSO) cross-validation on N images + normal training/test experiments. Note that only '''one''' training image is used for LOSO 2.
 
 
[[File:xu.17.icip-experiments.jpg|800 px]]
 
[[File:xu.17.icip-experiments.jpg|800 px]]
   

Revision as of 12:44, 6 February 2017

Method and datasets

Method

Architecture of the proposed network. We fine tune it and combine linearly fine to coarse feature maps of the pre-trained VGG network. The coarsest feature maps are discarded for the adult images. Xu.17.icip-pepeline.png

Datasets

  • Dataset of the MICCAI challenge of Neonatal Brain Segmentation 2012 (NeoBrainS12)
    • Axial images acquired at 40 weeks: 2 training images + 5 test images
    • Coronal images acquired at 30 weeks: 2 training images + 5 test images
    • Coronal images acquired at 40 weeks: 5 test images
  • Dataset of the MICCAI challenge of MR Brain Image Segmentation (MRBrainS13)
    • Axial images acquired at 70 years: 5 training images + 15 test images

Materials

Illustrations

Experiments

Leave-One-Subject-Out (LOSO) cross-validation on N images + normal training/test experiments. Note that only one training image is used for LOSO 2. Xu.17.icip-experiments.jpg

LOSO experiments

Axial 40 weeks in NeoBrainS12 dataset

Xu.17.icip-losoresults.jpg


Coronal 30 weeks in NeoBrainS12 dataset

Aging adult at 60 ages in MRBrainS13 dataset

Neonatal brain MR image segmentation

Xu.17.icip-axial40results.jpg


Xu.17.icip-coronal30results.jpg


Xu.17.icip-coronal40results.jpg


Adult brain MR image segmentation

Xu.17.icip-adult70results.jpg