Difference between revisions of "NeoBrainSeg"
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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.