harvardOxfordAtlasLabeling: Subcortical and cerebellar labeling from a T1 image.

In ANTsX/ANTsRNet: Neural Networks for Medical Image Processing

Subcortical and cerebellar labeling from a T1 image.

Description

Perform HOA labeling using deep learning and data from Morphology" number: "NIH NIMH 5R01MH112748-04". Repository: https://github.com/HOA-2/SubcorticalParcellations'

Usage

harvardOxfordAtlasLabeling(t1, doPreprocessing = TRUE, verbose = FALSE)

Arguments

t1	raw or preprocessed 3-D T1-weighted brain image.
doPreprocessing	perform preprocessing. See description above.
verbose	print progress.

Details

The labeling is as follows:

• Label 1:Lateral Ventricle Left

• Label 2:Lateral Ventricle Right

• Label 3:CSF

• Label 4:Third Ventricle

• Label 5:Fourth Ventricle

• Label 6:5th Ventricle

• Label 7:Nucleus Accumbens Left

• Label 8:Nucleus Accumbens Right

• Label 9:Caudate Left

• Label 10:Caudate Right

• Label 11:Putamen Left

• Label 12:Putamen Right

• Label 13:Globus Pallidus Left

• Label 14:Globus Pallidus Right

• Label 15:Brainstem

• Label 16:Thalamus Left

• Label 17:Thalamus Right

• Label 18:Inferior Horn of the Lateral Ventricle Left

• Label 19:Inferior Horn of the Lateral Ventricle Right

• Label 20:Hippocampal Formation Left

• Label 21:Hippocampal Formation Right

• Label 22:Amygdala Left

• Label 23:Amygdala Right

• Label 24:Optic Chiasm

• Label 25:VDC Anterior Left

• Label 26:VDC Anterior Right

• Label 27:VDC Posterior Left

• Label 28:VDC Posterior Right

• Label 29:Cerebellar Cortex Left

• Label 30:Cerebellar Cortex Right

• Label 31:Cerebellar White Matter Left

• Label 32:Cerebellar White Matter Right

Preprocessing on the training data consisted of:

• n4 bias correction,

• brain extraction, and

• affine registration to HCP. The input T1 should undergo the same steps. If the input T1 is the raw T1, these steps can be performed by the internal preprocessing, i.e. set doPreprocessing = TRUE

Value

list consisting of the segmentation image and probability images for each label.

Author(s)

Tustison NJ

Examples

## Not run: 
library( ANTsRNet )
library( keras )

image <- antsImageRead( "t1.nii.gz" )
results <- harvardOxfordAtlasLabeling( image )

## End(Not run)

ANTsX/ANTsRNet documentation built on Jan. 26, 2025, 2:55 p.m.