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A. El-Rafei, T. Engelhorn, S. Wärntges, J. Hornegger, G. Michelson, A. Dörfler; Automated Segmentation of the Optic Radiation Using Diffusion Tensor Imaging in Glaucoma Patients. Invest. Ophthalmol. Vis. Sci. 2009;50(13):321.
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© ARVO (1962-2015); The Authors (2016-present)
The goal of this work is to automatically segment the optic radiation in diffusion tensor images (DTI). This is an essential step to investigate the correlation between glaucoma and the optic radiation atrophy towards a better understanding of glaucoma.
MRI brain scans of eight subjects (mean age 65.8±14.8 years, four normal subjects and four glaucoma patients) using a 3 Tesla-MRI scanner were performed. The scans included T1, T2-weighted images and DTI. In order to volumetrically segment the optic radiation, first the DTI data were interpolated in the Log-Euclidean framework to avoid the tensor swelling effect. Then the data were filtered using a diffusion filtering technique to regularize the data while preserving the edges. The following step was to obtain an initial estimate of the optic radiation by performing an adaptive thresholding connectivity analysis. This step is based on the fact that the main tract of the optic radiation is characterized by diffusion in the anterior-posterior direction. In the segmentation stage, the initial segmentation was used as an input to the statistical level set framework developed in  using the Log-Euclidean framework. The used framework has the advantage that it incorporates the complete tensor information in a statistical framework to account for the uncertainties in DTI. Finally, the brain stem was segmented. The segmented optic radiation was adjusted according to its relative position to the segmented brain stem and the segmentation results were evaluated by a medical expert.
The main fiber bundles of the optic radiation and their pathway were efficiently determined. The results of the segmentation were found to be in agreement with the known anatomy of the optic radiation.
The proposed segmentation method uses the complete tensor information and incorporates anatomical information to produce robust results. Utilizing the coherence property within the fiber bundle of the optic radiation in the segmentation avoids the accumulated errors in tractography methods and is more suitable in segmenting fiber bundles. The automated segmentation algorithm was able to produce reliable results for the segmentation of the optic radiation. These results are the basis of a correlation study between the optic radiation atrophy and glaucoma.
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