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Medical ultrasound is widely used technique for diagnosing internal organs.As common artifacts, shadows often appear in ultrasound images. Detecting suchshadows is curious because they prevent accurate diagnosis. In this paper, wepropose a novel shadow detection method based on auto-encoding structure. Itonce separates an input image into a shadow image and a content image using twodecoders and combines them to reconstruct the input. To lead the network intoseparating the input, we inject synthetic shadows into the input and make thenetwork to predict them as the shadow image. Since we know the rough shape ofshadows as basic domain knowledge, we can generate plausible shadows. Theseprocesses are achieved by using only unlabeled data. Experiments on ultrasoundimages for fetal heart diagnosis shows the effectiveness of the method.

Shadow Detection for Ultrasound Images Using Unlabeled Data and Synthetic Shadows