NITRC: Arterial Atlas: ArterialAtlas

ArterialAtlas_v2 now is released

Posted By: CHIN LIU - Oct 13, 2021
Tool/Resource: Arterial Atlas

The atlas covers supra- and infra-tentorial regions and contains hierarchical segmentation levels created by a fusion of vascular and classical anatomical criteria. This deformable 3D digital atlas allows automatic and reproducible exploration of large-scaled data.

In this version, the following images are provided or updated.

* Images in “Atlas” folder are in MNI coordinates in 181x217x181 mm^3

* Images in “Atlas_182” folder in MNI coordinates in 182x218x182 mm^3 (compatible with FSL)

* Image descriptions:

ArterialAtlasLabels.txt: the “lookup table”.
It contains the labels (descriptive and acronyms) for the regions defined in ArterialAtlas.nii and ArterialAtlas_level2.nii.

ArterialAtlas.nii: Image defining 30 arterial territories and ventricles.
The intensities of the parcels correspond to their labels IDs, listed in the lookup table “ArterialAtlasLabels.txt

ArterialAtlas_level2.nii: The combination of ArterialAtlas.nii parcels in 4 major territories (ACA, MCA, PCA, VB).
The intensities of the parcels correspond to their labels, listed in the ArterialAtlasLabels.txt

ProbArterialAtlas_average.nii: 4D image of the arterial territory maps, calculated by averaging of lesion masks.
Each dimension represents the probability of a voxel to belong to a certain vascular territory (ACA, MCA, PCA, VB, respectively).

ProbArterialAtlas_BMM.nii: 4D image of the arterial territory maps, calculated by the Bernoulli Mixture Model(BMM) method.
Each dimension represents the probability of a voxel to belong to a certain vascular territory (ACA, MCA, PCA, VB, respectively).

BorderZone_ProbAve.nii: 4D image showing the ratio of average probability maps;
first dimension is MCA / ACA, second dimension is MCA / PCA.

TerritoryVoxels_BMM.nii: 3D image showing the assignment of voxels to major vascular territories, calculated through the variation in BMM µmax.
The image intensities are: 1. ACA, 2. MCA, 3. PCA, 4. voxels attributed to more than one vascular territory, 5. voxels not attributed to any vascular territory.