White matter lesion extension to automatic brain tissue segmentation on MRI

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Evaluation of a deep learning approach for the segmentation of brain tissues and white matter hyperintensities of presumed vascular origin in MRI (2017, unknown): “…Klöppel et al., 2011; Steenwijk et al., 2013; Ghafoorian et al., 2016) or detection of WMH as outliers of tissue segmentation (Van Leemput et al., 2001; De Boer et al., 2009; Schmidt et al., 2012; Sudre et al., 2014; Sudre et al., 2015; Roura et al., 2015; Jain et al., 2015; Kuijf et al., 2016).”
A review of atlas-based segmentation for magnetic resonance brain images (2011, methodology): “854 using only 3 cases) and general white matter lesions [93] (DSC of 0.”
BIANCA (Brain Intensity AbNormality Classification Algorithm): A new tool for automated segmentation of white matter hyperintensities (2016, methodology): “For WMH, several segmentation algorithms exist (Admiraal-Behloul et al., 2005; Anbeek et al., 2004; de Boer et al., 2009; DeCarli et al., 1995; Dyrby et al., 2008; Ramirez et al., 2011), and a recent review by Caligiuri and colleagues (Caligiuri et al., 2015) compared different existing algorithms.”