Limits...
Voxel-based texture analysis of the brain.

Maani R, Yang YH, Kalra S - PLoS ONE (2015)

Bottom Line: The proposed method provides a 3D statistical map comparing texture features on a voxel-by-voxel basis.The proposed method detected artificial effects with high accuracy and revealed statistically significant differences between the AD and control groups.This paper extends the usage of texture analysis beyond the current region of interest analysis to voxel-by-voxel 3D statistical mapping and provides a hypothesis-free analysis tool to study cerebral pathology in neurological diseases.

View Article: PubMed Central - PubMed

Affiliation: Department of Computing Science, University of Alberta, Edmonton, Canada.

ABSTRACT
This paper presents a novel voxel-based method for texture analysis of brain images. Texture analysis is a powerful quantitative approach for analyzing voxel intensities and their interrelationships, but has been thus far limited to analyzing regions of interest. The proposed method provides a 3D statistical map comparing texture features on a voxel-by-voxel basis. The validity of the method was examined on artificially generated effects as well as on real MRI data in Alzheimer's Disease (AD). The artificially generated effects included hyperintense and hypointense signals added to T1-weighted brain MRIs from 30 healthy subjects. The AD dataset included 30 patients with AD and 30 age/sex matched healthy control subjects. The proposed method detected artificial effects with high accuracy and revealed statistically significant differences between the AD and control groups. This paper extends the usage of texture analysis beyond the current region of interest analysis to voxel-by-voxel 3D statistical mapping and provides a hypothesis-free analysis tool to study cerebral pathology in neurological diseases.

Show MeSH

Related in: MedlinePlus

Schematic Venn diagram illustrating different possible regions considered for a detected region and an artificial lesion.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4355627&req=5

pone.0117759.g003: Schematic Venn diagram illustrating different possible regions considered for a detected region and an artificial lesion.

Mentions: To evaluate the validity of the proposed voxel-based texture analysis a database of artificial effects was used. In addition to detection rate which shows what percentages of the artificial lesions are correctly identified, three extra measurements were determined: Jaccard coefficient, false negative error, and false positive error. The schematic Venn diagram in Fig. 3 is used to illustrate the derivation of these measures. Assume that texture features detect region “D” as the lesion while the exact lesion region is “L”. The voxels that are in “D” but not in “L” are denoted by “D\L” and the voxels that are in “L” but not in “D” are denoted by “L\D”.


Voxel-based texture analysis of the brain.

Maani R, Yang YH, Kalra S - PLoS ONE (2015)

Schematic Venn diagram illustrating different possible regions considered for a detected region and an artificial lesion.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4355627&req=5

pone.0117759.g003: Schematic Venn diagram illustrating different possible regions considered for a detected region and an artificial lesion.
Mentions: To evaluate the validity of the proposed voxel-based texture analysis a database of artificial effects was used. In addition to detection rate which shows what percentages of the artificial lesions are correctly identified, three extra measurements were determined: Jaccard coefficient, false negative error, and false positive error. The schematic Venn diagram in Fig. 3 is used to illustrate the derivation of these measures. Assume that texture features detect region “D” as the lesion while the exact lesion region is “L”. The voxels that are in “D” but not in “L” are denoted by “D\L” and the voxels that are in “L” but not in “D” are denoted by “L\D”.

Bottom Line: The proposed method provides a 3D statistical map comparing texture features on a voxel-by-voxel basis.The proposed method detected artificial effects with high accuracy and revealed statistically significant differences between the AD and control groups.This paper extends the usage of texture analysis beyond the current region of interest analysis to voxel-by-voxel 3D statistical mapping and provides a hypothesis-free analysis tool to study cerebral pathology in neurological diseases.

View Article: PubMed Central - PubMed

Affiliation: Department of Computing Science, University of Alberta, Edmonton, Canada.

ABSTRACT
This paper presents a novel voxel-based method for texture analysis of brain images. Texture analysis is a powerful quantitative approach for analyzing voxel intensities and their interrelationships, but has been thus far limited to analyzing regions of interest. The proposed method provides a 3D statistical map comparing texture features on a voxel-by-voxel basis. The validity of the method was examined on artificially generated effects as well as on real MRI data in Alzheimer's Disease (AD). The artificially generated effects included hyperintense and hypointense signals added to T1-weighted brain MRIs from 30 healthy subjects. The AD dataset included 30 patients with AD and 30 age/sex matched healthy control subjects. The proposed method detected artificial effects with high accuracy and revealed statistically significant differences between the AD and control groups. This paper extends the usage of texture analysis beyond the current region of interest analysis to voxel-by-voxel 3D statistical mapping and provides a hypothesis-free analysis tool to study cerebral pathology in neurological diseases.

Show MeSH
Related in: MedlinePlus