Automatic Multi-Modality Segmentation of White Matter Hyperintensities Using a Random Forests Classifier
نویسندگان
چکیده
All the images are first preprocessed in three steps: I) noise reduction [1], II) intensity nonuniformity correction [2] and III) linear intensity normalization into range (0-100) using an intensity histogram matching technique. The T1w and FLAIR images are linearly co-registered using a 6 parameter rigid registration [3]. The T1w images are first linearly and then nonlinearly registered to an average template created based on data from the ADNI1 study [4], enabling the use of anatomical priors in the segmentation process. A brain mask is created by warping the template mask back to the individual’s native space.
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