Authors: Brittany Reiche Alan R Moody April Khademi
Publish Date: 2015/10/26
Volume: 9, Issue: 1, Pages: 11-16
Abstract
Fluid attenuation inversion recovery FLAIR magnetic resonance images MRI are being used by physicians to identify and analyze white matter lesions in the brain to determine whether patients are at risk of stroke Pipelines used to analyze these images require a preprocessing step of brain extraction in order to be robust and to be applied to multicenter largescale studies This paper proposes a novel brain extraction tool solely for the FLAIR modality as well as a robust standardization pipeline that eliminates variability between datasets by reducing image noise intensity inhomogeneity patient movement and the nonstandardness of tissue intensities which are inherent in MRI Feature extraction is performed on the standardized dataset and a brain segmentation is produced by a random forest classifier The effects of the standardization steps are evaluated using objective metrics and the resultant segmentations produced by the unstandardized and standardized images are compared By implementing a robust standardization pipeline images acquired from different scanners at different centers can be processed automatically and accurately allowing for the fast processing of largescale multicenter dataThis paper is dedicated to Dr Anastasios Venetsanopoulos a true leader in image processing His advancement of the field and training of the next generation of engineers has had enormous impact on the image processing community His leadership mentorship and friendship will be sorely missed
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