mia-3dbrainextractT1 {-i io} {-o io} [ options ...]


This program is used to extract the brain from T1 MR images. It first runs a combined fuzzy c-means clustering and B-field correction to facilitate a 3D segmentation of 3D image. Then various fiters are run to obtain a white matter segmentation as initial mask that is then used to run a region growing to obtain a mask of the whole brain. Finally, this mask is used to extact the brain from the B0 field corrected images.


-i, --in-file=(input, required); io

input image(s) to be segmented. For supported file types see Plugin type: 3dimage/io

-o, --out-file=(output, required); io

brain mask. For supported file types see Plugin type: 3dimage/io

-n, --no-of-classes=3; int

number of classes

-w, --wm-class=2; int

index of white matter

-p, --wm-prob=0.7; float

white matter class probability for initial mask creation

-t, --grow-threshold=20; int

intensity threshold for region growing

--grow-shape=18n; stringSTRING

neighbourhood mask region growing

Help & Info

-V, --verbose=warning; dict

verbosity of output, print messages of given level and higher priorities. Supported priorities starting at lowest level are:

info:Low level messages
trace:Function call trace
fail:Report test failures
error:Report errors
debug:Debug output
message:Normal messages
fatal:Report only fatal errors
--copyright=(); bool

print copyright information

-h, --help=(); bool

print this help

-?, --usage=(); bool

print a short help

--version=(); bool

print the version number and exit


--threads=-1; int

Maxiumum number of threads to use for processing,This number should be lower or equal to the number of logical processor cores in the machine. (-1: automatic estimation).


Create a mask from the input image by running a 5-class segmentation over inpt image input.v and use class 4 as white matter class and store the masked image in masked.v and the B0-field corrected image in b0.v

mia-3dbrainextractT1 -i input.v -n 5 -w 4 -o masked.v


Gert Wollny