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

From LRDE

(Neonatal brain MR image segmentation)
(Adult brain MR image segmentation)
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Some qualitative results
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Some result images
 
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File:Xu.17.icip-mrbrainsTest514Input.png
 
File:Xu.17.icip-mrbrainsTest514Input.png

Revision as of 23:04, 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

Trained models

The trained models and corresponding files for training for the proposed method on NeoBrainS12 and MRBrainS13 datasets are available in the following:

  • Training on Axial images at 40 weeks in NeoBrainS12 dataset are available in this archive
  • Training on coronal images at 30 weeks in NeoBrainS12 dataset are available in this archive
  • Training on previous training sets for coronal images at 40 weeks in NeoBrainS12 dataset are available in this archive
  • Training on MRBrainS13 dataset is available in this archive

Segmentation results

The pre-computed segmentation results of the proposed method on NeoBrainS12 and MRBrainS13 datasets are available in the following:

  • Results on Axial images at 40 weeks in NeoBrainS12 dataset are available in this archive
  • Results on coronal images at 30 weeks in NeoBrainS12 dataset are available in this archive
  • Results on coronal images at 40 weeks in NeoBrainS12 dataset are available in this archive
  • Results on MRBrainS13 dataset are available in this archive

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

Quantitative results of LOSO experiments in terms of Dice coefficient as compared to the state-of-the-art results. The last one is from P. Moeskops et al. on the 15 test images in MRBrainS13 dataset.

Xu.17.icip-losoresults.jpg

  • Some results on axial images at 40 weeks in NeoBrainS12 dataset
  • Some results on coronal images at 30 weeks in NeoBrainS12 dataset
  • Some results on axial images of aging adults at 70 ages in MRBrainS13 dataset

Neonatal brain MR image segmentation

  • Results on axial images at 40 weeks in NeoBrainS12 dataset. More details can be found Here

Xu.17.icip-axial40results.jpg

Some result images


  • Results on coronal images at 30 weeks in NeoBrainS12 dataset. More details can be found Here

Xu.17.icip-coronal30results.jpg

Some result images (some small errors inside the red circle)


  • Results on coronal images at 40 weeks in NeoBrainS12 dataset. More details can be found Here

Xu.17.icip-coronal40results.jpg

Some result images (some small errors inside red circles)

Adult brain MR image segmentation

  • Results on aging adult images at 70 years in MRBrainS13 dataset. Only top 10 methods among 38 submitted ones are shown. More results and details can be found Here

Xu.17.icip-adult70results.jpg

Some result images