Figure 6
Image reconstructions of a median-size breast (14.5Ā cm chest wall diameter). Incomplete projection data were reconstructed using FDK with Parker weight, FDK with offset-detector weight (denoted as FDK-M), and two fully supervised learning (FSL) methods, whose network inputs were either of the two weighted FDK reconstructions. The incomplete data were inpainted by AFN and further reconstructed by FDK-M. Complete projection data were reconstructed using FDK to obtain the reference (last column). Using the images reconstructed by FDK w/ Parker weight (column 1), FSL (column 2) alleviates the truncation artifacts indicated by the red arrows in column 1 yet creates additional artifacts as indicated by the yellow arrows in column 2. Similarly, using the images reconstructed by FDK w/ offset-detector weight (column 3), FSL (column 4) addresses the non-homogeneity indicated by the red arrows in column 3 yet generates severe artifacts as indicated by the yellow arrows in column 4. In contrast, reconstructions using AFN inpainted data (column 5) are visually similar to the reference in column 6. The display window is [0.15, 0.35] cmā1.
