sct_deepseg_sc¶
Spinal Cord Segmentation using convolutional networks. Reference: Gros et al. Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks. Neuroimage. 2019 Jan 1;184:901-915.
usage: sct_deepseg_sc -i <file> -c {t1,t2,t2s,dwi} [-h]
[-centerline {svm,cnn,viewer,file}]
[-file_centerline <str>] [-thr <float>] [-brain {0,1}]
[-kernel {2d,3d}] [-ofolder <str>] [-o <file>] [-r {0,1}]
[-v <int>] [-qc <str>] [-qc-dataset <str>]
[-qc-subject <str>]
MANDATORY ARGUMENTS¶
- -i
Input image. Example:
t1.nii.gz
- -c
Possible choices: t1, t2, t2s, dwi
Type of image contrast.
OPTIONAL ARGUMENTS¶
- -centerline
Possible choices: svm, cnn, viewer, file
Method used for extracting the centerline:
svm
: Automatic detection using Support Vector Machine algorithm.cnn
: Automatic detection using Convolutional Neural Network.viewer
: Semi-automatic detection using manual selection of a few points with an interactive viewer followed by regularization.file
: Use an existing centerline (use with flag-file_centerline
)
Default: “svm”
- -file_centerline
Input centerline file (to use with flag
-centerline
file). Example:t2_centerline_manual.nii.gz
- -thr
Binarization threshold (between
0
and1
) to apply to the segmentation prediction. Set to-1
for no binarization (i.e. soft segmentation output). The default threshold is specific to each contrast and was estimated using an optimization algorithm. More details at: https://github.com/sct-pipeline/deepseg-threshold.- -brain
Possible choices: 0, 1
Indicate if the input image contains brain sections (to speed up segmentation). Only use with
-centerline cnn
. (default:1
for T1/T2 contrasts,0
for T2*/DWI contrasts)- -kernel
Possible choices: 2d, 3d
Choice of kernel shape for the CNN. Segmentation with 3D kernels is slower than with 2D kernels.
Default: “2d”
- -ofolder
Output folder. Example:
My_Output_Folder
Default: “/home/docs/checkouts/readthedocs.org/user_builds/spinalcordtoolbox/checkouts/stable/documentation/source”
- -o
Output filename. Example:
spinal_seg.nii.gz
- -r
Possible choices: 0, 1
Remove temporary files.
Default: 1
- -v
Possible choices: 0, 1, 2
Verbosity. 0: Display only errors/warnings, 1: Errors/warnings + info messages, 2: Debug mode
Default: 1
- -qc
The path where the quality control generated content will be saved
- -qc-dataset
If provided, this string will be mentioned in the QC report as the dataset the process was run on
- -qc-subject
If provided, this string will be mentioned in the QC report as the subject the process was run on