English: Figure 8 from Andreas Maier, Christopher Syben. Tobias Lasser. Christian Riess. "A gentle introduction to deep learning in medical image processing". Zeitschrift für Medizinische Physik

Volume 29, Issue 2, May 2019, Pages 86-101.

https://www.sciencedirect.com/science/article/pii/S093938891830120X

Please reference this article, if you reuse this figure.

Original Caption: Results from a deep learning image-to-image reconstruction based on U-net. The reference image with a lesion embedded is shown on the left followed by the analytic reconstruction result that is used as input to U-net. U-net does an excellent job when trained and tested without noise. If unmatched noise is provided as input, an image is created that appears artifact-free, yet not just the lesion is gone, but also the chest surface is shifted by approximately 1 cm. On the right hand side, an undesirable result is shown that emerged at some point during training of several different versions of U-net which shows organ-shaped clouds in the air in the background of the image. Note that we omitted displaying multiple versions of “Limited Angle” as all three inputs to the U-Nets would appear identically given the display window of the figure of [−1000, 1000] HU.