Skip to main content
. Author manuscript; available in PMC: 2021 Jun 1.
Published in final edited form as: Magn Reson Imaging. 2020 Mar 13;69:49–56. doi: 10.1016/j.mri.2020.03.002

Fig. 1.

Fig. 1.

Schema for brain tumor segmentation and radiomic feature extraction. (A) Representative images of post contrast T1-weighted (T1C) and fluid-attenuated inversion recovery (FLAIR) images. (B) Segmented enhancing tumor and peritumoral edema masks (top panel) overlapping the T1C images (middle panel) and FLAIR images (bottom panel). (C) Illustrations of the three categories of radiomic features extracted from the images, including shape, intensity, and texture. GLCM: Gray Level Co-occurrence Matrix; GLRLM: Gray Level Run Length Matrix; GLSZM: Gray Level Size Zone Matrix; NGTDM: Neighboring Gray Tone Difference Matrix. (D) The left panel indicates the top 50 radiomic features used for classifying each of the three types of mutation status. The right panel shows the receiver operating characteristic curves for classifying the three types of mutation status.