Difference between revisions of "NeoBrainSeg"

From LRDE

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= The Challenge of Cerebral MRI in Neonates: A New Method using Mathematical Morphology for the Segmentation of Structures Including DEHSI =
 
= The Challenge of Cerebral MRI in Neonates: A New Method using Mathematical Morphology for the Segmentation of Structures Including DEHSI =

Revision as of 13:25, 26 July 2018

The Challenge of Cerebral MRI in Neonates: A New Method using Mathematical Morphology for the Segmentation of Structures Including DEHSI

Publication

The related publication is available from this page.

Bibtex entry:

@Article{xu.18.media,
  author = {Yongchao Xu and Baptiste Morel and Sonia Dahdouh and
            \'Elodie Puybareau and Alessio Virz\`i and H\'el\`ene
            Urien and Thierry~G\'eraud and Catherine Adamsbaum and
            Isabelle Bloch},
  title  = {The Challenge of Cerebral Magnetic Resonance Imaging in
            Neonates: {A} New Method using Mathematical Morphology
            for the Segmentation of Structures Including Diffuse
            Excessive High Signal Intensities},
  journal = {Medical Image Analysis},
  year    = 2018,
  pages   = {1--23},
  url     = {http://publications.lrde.epita.fr/xu.18.media},
  note    = {To appear}
}

Software

software_NeoBrainSeg.zip (939Mo)

If this software is used in the context of a scientific publication, please cite the paper mentioned above.

Copyright Notice

The copyright holders of the main code included in the archive are:

  • EPITA Research and Development Laboratory (LRDE)
  • LTCI Télécom ParisTech
  • Faculty of Medicine Bicêtre Hospital APHP
  • Faculty of Medicine CHRU Tours.

You are allowed to use these codes and software for research purpose. If so, please specify the following copyright: "Copyright (c) 2018. EPITA Research and Development Laboratory (LRDE)". You are not allowed to redistribute these codes. You are not allowed to redistribute the dehsi.nii example.




White Matter Hyperintensities Segmentation In a Few Seconds Using FCN and Transfer Learning

Publication

The related publication is available from this page.

Bibtex entry:

@InProceedings{xu.18.brainles,
  author    = {Yongchao Xu and Thierry G{\'e}raud and {\'E}lodie
               Puybareau and Isabelle Bloch and Joseph Chazalon},
  title     = {White Matter Hyperintensities Segmentation In a Few
               Seconds Using Fully Convolutional Network and Transfer
               Learning},
  booktitle = {Brainlesion: Glioma, Multiple Sclerosis, Stroke and
               Traumatic Brain Injuries--- 3rd International Workshop,
               BrainLes 2017, Held in Conjunction with MICCAI 2017,
               Quebec City, QC, Canada, September 14 2017, Revised
               Selected Papers},
  publisher = {Springer, Cham},
  year      = {2018},
  editor    = {A. Crimi and S. Bakas and H. Kuijf and B. Menze and
               M. Reyes},
  series    = {Lecture Notes in Computer Science},
  volume    = {10670},
  pages     = {501--514},
  doi       = {10.1007/978-3-319-75238-9_42},
  url       = {http://publications.lrde.epita.fr/xu.18.brainles},
}

Software

LRDE.tar.zip (1.3Go)

If this software is used in the context of a scientific publication, please cite the paper mentioned above.

The software is provided as a Docker container. Just run:

CONTAINERID=`docker run -dit -v [TEST-ORIG]:/input/orig:ro -v [TEST-PRE]:/input/pre:ro -v /output wmhchallenge/LRDE`
docker exec $CONTAINERID [YOUR-COMMAND]
docker cp $CONTAINERID:/output [RESULT-TEAM]
docker stop $CONTAINERID
docker rm -v $CONTAINERID

Two folders are needed in your local folder: the entry data (FLAIR and T1) should be in input/pre, and the result will be written in output. This docker has been done for the MICCAI 2017 challenge: http://wmh.isi.uu.nl/



iSeg: MICCAI Grand Challenge on 6-month infant brain MRI Segmentation

Publication

A review article of the challenge will be available soon.

Software

Challenge_iSeg.zip (28.9Mo)

If this software is used in the context of a scientific publication, please cite the paper mentioned above.

Copyright Notice

The copyright holders of the main code included in the archive are:

  • EPITA Research and Development Laboratory (LRDE)
  • LTCI Télécom ParisTech
  • Huazhong University of Science and Technology, Wuhan, China

You are allowed to use these codes and software for research purpose. If so, please specify the following copyright: "Copyright (c) 2018. EPITA Research and Development Laboratory (LRDE)". You are not allowed to redistribute these codes.