Version Release Notes
First version: 08.24.2012
Current version: 10.15.2018
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Fixed flipping in output DICOM’s, affecting MaskFace.12.27.2017.nomatlab.lin64.zip distribution.
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A Docker image supporting XNAT 1.7 container service is released. Docker image: https://hub.docker.com/r/mohanar/facemasking. Container service command: https://bitbucket.org/mohanar_radiologics/radiologics_containers
New in version 12.27.2017:
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A version that works using Matlab Runtime Environment (no Matlab license required) is released.
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Fixes to work correctly on Ubuntu machines
New in version 01.24.2014:
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Reworked the structure of the script into procedure-based
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The script now accepts multiple scans to process with the same parameters.
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The following modes of face masking are allowed by script
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based on FSL-coregistered coordinates file (generated by fsl after coregistration)
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based on supplied ROI coordinate file
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based on explicitly supplied ROI coordinates
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based on the reference scan
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each masking region requires a separate run of mask_surf_auto.m
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3D snapshots
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tweaked brain mask application to exclude more boundary voxels
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better support of anisotropic voxels
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added ear masking
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major updates to the face masking xnat pipeline:
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new parameters:
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ref: reference scan
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use_manual_roi: signal that manual ROI will be used instead of auto-registration.
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rois: specification of manual ROI’s
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dirs: ROI normal direction (s)
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step 0: scan lists are converted to be used with xnat2loc
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step 1: xnat2loc is now used to download and process DICOM scans instead of XNATRestClient.
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new face masking script takes a list of scans, reference and ROI parameters as input.
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Usage
mask_face <image>[,<image>..] [options]
The first argument must list one or more MR head image files. If more than one image is specified, you must also specify one of them as reference with -r option. The reference image will be used for spatial co-registration with an atlas, and others will use the reference facial mask.
By default, the input is the DICOM directory of a single series. You can also supply images in Analyze/NIFTI (.hdr/.img pair) format by adding -a option. The output and input formats are the same.
Options
For the complete set of options, run mask_face without parameters.
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Flag |
Description |
|---|---|
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-a |
Required if you are supplying images in Analyze/NIFTI (.hdr/.img pair) format |
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-m <method> |
Method used (coating, blur, normfilter, all):
|
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-t <threshold>
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Mask threshold: Threshold is selected automatically (recommended), but can be changed with this option |
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-s <grid_step> |
Grid Step: Larger grid step will result in coarser looking 3D renderings, and tends to modify more voxels outside of the immediate near-surface |
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-v <#> |
Control the amount of intermediate output:
|
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-b |
Generate the brain mask used by FSL's bet algorithm prior to face masking and use it to exclude brain voxels from modification |
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-e <#> |
Controls ear-masking.
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-um <#> |
Toggles the use of manual ROI coordinates
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-r <image> |
Required if more than one image is being defaced. The reference image will be used for spatial co-registration with an atlas, and others will use the reference facial mask. (Use the highest quality image for your reference.) |
References
The algorithm main paper:
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Milchenko, M. V. & Marcus, D. (2012). Obscuring surface anatomy in volumetric imaging data. Neuroinformatics. doi: 10.1007/s12021-012-9160-3