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Fig. 2 | BMC Medical Imaging

Fig. 2

From: Cerebral morphometric alterations predict the outcome of migraine diagnosis and subtyping: a radiomics analysis

Fig. 2

Six identified connectivity features to discriminate migraine patients from HCs, using the all-relevant feature selection algorithm. These features were listed as follows: the skewness of convexity in thalamus (A) the mean of local thickness (LT) in postcentral sulcus (B) the kurtosis of mean diffusivity (MD) in insula (C) the kurtosis of mean curvature (MC) in postcentral (D) the skewness of travel depth (TD) in caudal middle frontal (E) the standard deviation (SD) of fractional anisotropy (FA) in inferior parietal (F). They all showed significant differences between patients and HC. Statistical significance is indicated by asterisks (***, P < 0.001; **, P < 0.01)

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BMC Medical Imaging

ISSN: 1471-2342

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