  As an important scan plane, four chamber view is routinely performed in both
second trimester perinatal screening and fetal echocardiographic examinations.
The biometrics in this plane including cardio-thoracic ratio (CTR) and cardiac
axis are usually measured by sonographers for diagnosing congenital heart
disease. However, due to the commonly existing artifacts like acoustic
shadowing, the traditional manual measurements not only suffer from the low
efficiency, but also with the inconsistent results depending on the operators'
skills. In this paper, we present an anchor-free ellipse detection network,
namely EllipseNet, which detects the cardiac and thoracic regions in ellipse
and automatically calculates the CTR and cardiac axis for fetal cardiac
biometrics in 4-chamber view. In particular, we formulate the network that
detects the center of each object as points and regresses the ellipses'
parameters simultaneously. We define an intersection-over-union loss to further
regulate the regression procedure. We evaluate EllipseNet on clinical
echocardiogram dataset with more than 2000 subjects. Experimental results show
that the proposed framework outperforms several state-of-the-art methods.
Source code will be available at https://git.openi.org.cn/capepoint/EllipseNet .
