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• W2169871331 abstract "Diffusion tensor imaging (DTI) has been advocated as a promising tool for delineation of the extent of tumor infiltration by primary brain tumors. First reports show conflicting results mainly due to difficulties in reproducible determination of DTI-derived parameters. A novel method based on probabilistic voxel classification for a user-independent analysis of DTI-derived parameters is presented and tested in healthy controls and patients with primary brain tumors. The proposed quantification method proved to be highly reproducible both in healthy controls and patients. Fiber integrity in the corpus callosum (CC) was measured using this quantification method, and the profiles of fractional anisotropy (FA) provided additional information of the possible extent of infiltration of primary brain tumors when compared to conventional imaging. This yielded additional information on the nature of ambiguous contralateral lesions in patients with primary brain tumors. The results show that DTI-derived parameters can be determined reproducibly and may have a strong impact on evaluation of contralateral extent of primary brain tumors." @default.
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• W2169871331 date "2006-06-01" @default.
• W2169871331 modified "2023-10-17" @default.
• W2169871331 title "Diffusion tensor imaging in primary brain tumors: Reproducible quantitative analysis of corpus callosum infiltration and contralateral involvement using a probabilistic mixture model" @default.
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• W2169871331 doi "https://doi.org/10.1016/j.neuroimage.2005.12.052" @default.
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