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

Image and Video Processing