Voxel-wise deep learning segmentation of hydroxyapatite and iodine in spectral photon-counting CT: A quantitative phantom study
Fig 2
Overview of the phantom datasets and augmentation.
Left: matrix view with scans as rows and energy bins (E1 to E5) as columns. Right: grid puzzle augmentation on a representative slice; the original grayscale DICOM image and the corresponding ground truth (voxels color-coded by class) are shown.