Examples of radiomic features extracted from cardiac MR images (T1 mapping in this example) in a 62-year-old female patient by using PyRadiomics. (a) Cardiac MR image and the manually delineated ROI were given as inputs, and image filters were applied on the original image to create additional radiomic features. (b) A total of 1023 features were extracted from various feature families. GLCM = gray-level co-occurrence matrix, GLDM = gray-level dependence matrix, GLRLM = gray-level run length matrix, GLSZM = gray-level size-zone matrix, LBP = local binary pattern, NGTDM = neighboring gray-tone-difference matrix, ROI = region of interest, wavelet-HH = wavelet high-pass filter applied in horizontal and vertical directions, wavelet-HL = wavelet high- and low-pass filters applied in horizontal and vertical directions, wavelet-LH = wavelet low- and high-pass filters applied in horizontal and vertical directions, wavelet-LL = wavelet low-pass filter applied in horizontal and vertical directions.