Difference between revisions of "Brain ventricle parcellation instructions"

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(Created page with "<meta name="title" content="Brain Ventricle Parcellation with Convolutional Neural Network"/> {{h2|Brain Ventricle Parcellation with Convolutional Neural Network}} This singul...")
 
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{{h2|Brain Ventricle Parcellation with Convolutional Neural Network}}
 
{{h2|Brain Ventricle Parcellation with Convolutional Neural Network}}
 
This singularity image contains the code and trained model for brain ventricle parcellation using a convolutional neural network. If you use this work, please cite:
 
This singularity image contains the code and trained model for brain ventricle parcellation using a convolutional neural network. If you use this work, please cite:
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*Shao, M., Han, S., Carass, A., Li, X., Blitz, A.M., Shin, J., Prince, J.L. and Ellingsen, L.M., 2019. '''Brain ventricle parcellation using a deep neural network: Application to patients with ventriculomegaly'''. NeuroImage: Clinical, p.101871.
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If you have any questions, please email Muhan Shao at <code>muhan@jhu.edu</code>.
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{{h3|Processing steps}}
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The singularity takes T1-w RAW brain MRI (nifti file) as input and performs the following steps:
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* N4 bias field correction from [http://stnava.github.io/ANTs/ ANTs]. The bias field is estimated using a weight image calculated from a brain mask generated by [https://www.nitrc.org/projects/robex ROBEX].
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* Rigid registration to [http://www.bic.mni.mcgill.ca/ServicesAtlases/ICBM152NLin2009 ICBM2009c] nonlinear symmetric template using the ANTs package. The template images were resampled to have resolution of 0.8x0.8x0.8mm.
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* Skull-stripping using ROBEX.
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* Brain ventricle parcellation on the skull-stripped MNI-registered T1-w MRI using the method described in "Shao, M., et al., 2019. Brain ventricle parcellation using a deep neural network: Application to patients with ventriculomegaly. NeuroImage: Clinical, p.101871".
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* The parcellation is transformed back to the original space using ANTs with the "MultiLabel" interpolation.
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{{h3|Output file structures}}
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The processing will create subfolders '''<code>n4/</code>''', '''<code>mni/</code>''',  and '''<code>parc/</code>''' under the output folder. The final parcellation result is directly under the output folder.
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* '''<code>*n4.nii.gz</code>''' is the bias field corrected image
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* '''<code>*n4_mni.nii.gz</code>''' is the image in the MNI space
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* '''<code>*n4_mni_strip.nii.gz</code>''' is the skull-stripped image
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* '''<code>*n4_mni_strip_seg.nii.gz</code>''' is the parcellation from the convolutional neural networks
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* '''<code>*n4_mni_strip_seg_inverse.nii.gz</code>''' is the final parcellation result in the original image space.
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{{h3|Installation}}
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* Install [https://www.sylabs.io/guides/2.6/user-guide/installation.html Singularity 2.6]
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{{h3|Usage}}
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* The Singularity image can only run on '''CPU''' although [https://www.tensorflow.org TensorFlow] and [https://keras.io Keras] are used, because the Singularity image only contains the CPU version of TensorFlow.
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* Assume that the Singularity image is <code>/path/to/simg/ventricle-parcellation.simg</code>, the image to parcellate is <code>~/image.nii.gz</code>, and the output folder is <code>~/output</code>
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singularity run /path/to/simg/ventricle-parcellation.simg -i ~/image.nii.gz -o ~/output
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* If the <code>image.nii.gz</code> is under <code>/path/to/image</code> which is not under your home directory
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singularity run -B /path/to/image:/mnt /path/to/simg/ventricle-parcellation.simg -i /mnt/image.nii.gz -o /mnt/output
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* Print help
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singularity run ~/ventricle-parcellation.simg -h
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{{h3|Brain ventricle labels}}
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    "51":  "Right lateral ventricle",
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    "52":  "Left lateral ventricle",
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    "4":  "third ventricle",
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    "11":  "fourth ventricle"

Revision as of 23:12, 25 April 2020

<meta name="title" content="Brain Ventricle Parcellation with Convolutional Neural Network"/>

Brain Ventricle Parcellation with Convolutional Neural Network

This singularity image contains the code and trained model for brain ventricle parcellation using a convolutional neural network. If you use this work, please cite:

  • Shao, M., Han, S., Carass, A., Li, X., Blitz, A.M., Shin, J., Prince, J.L. and Ellingsen, L.M., 2019. Brain ventricle parcellation using a deep neural network: Application to patients with ventriculomegaly. NeuroImage: Clinical, p.101871.

If you have any questions, please email Muhan Shao at muhan@jhu.edu.

Processing steps

The singularity takes T1-w RAW brain MRI (nifti file) as input and performs the following steps:

  • N4 bias field correction from ANTs. The bias field is estimated using a weight image calculated from a brain mask generated by ROBEX.
  • Rigid registration to ICBM2009c nonlinear symmetric template using the ANTs package. The template images were resampled to have resolution of 0.8x0.8x0.8mm.
  • Skull-stripping using ROBEX.
  • Brain ventricle parcellation on the skull-stripped MNI-registered T1-w MRI using the method described in "Shao, M., et al., 2019. Brain ventricle parcellation using a deep neural network: Application to patients with ventriculomegaly. NeuroImage: Clinical, p.101871".
  • The parcellation is transformed back to the original space using ANTs with the "MultiLabel" interpolation.

Output file structures

The processing will create subfolders n4/, mni/, and parc/ under the output folder. The final parcellation result is directly under the output folder.

  • *n4.nii.gz is the bias field corrected image
  • *n4_mni.nii.gz is the image in the MNI space
  • *n4_mni_strip.nii.gz is the skull-stripped image
  • *n4_mni_strip_seg.nii.gz is the parcellation from the convolutional neural networks
  • *n4_mni_strip_seg_inverse.nii.gz is the final parcellation result in the original image space.

Installation

Usage

  • The Singularity image can only run on CPU although TensorFlow and Keras are used, because the Singularity image only contains the CPU version of TensorFlow.
  • Assume that the Singularity image is /path/to/simg/ventricle-parcellation.simg, the image to parcellate is ~/image.nii.gz, and the output folder is ~/output
singularity run /path/to/simg/ventricle-parcellation.simg -i ~/image.nii.gz -o ~/output
  • If the image.nii.gz is under /path/to/image which is not under your home directory
singularity run -B /path/to/image:/mnt /path/to/simg/ventricle-parcellation.simg -i /mnt/image.nii.gz -o /mnt/output
  • Print help
singularity run ~/ventricle-parcellation.simg -h


Brain ventricle labels

   "51":  "Right lateral ventricle",
   "52":  "Left lateral ventricle",
   "4":  "third ventricle",
   "11":  "fourth ventricle"
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