Sequential anatomy localization in fetal echocardiography videos

Understand

Fetal heart motion is an important diagnostic indicator for structural detection and functional assessment of congenital heart disease.

• We propose an approach towards integrating deep convolutional and recurrent architectures that utilize localized spatial and temporal features of different anatomical substructures within a global spatiotemporal context for interpretation of fetal echocardiography videos.
• We formulate our task as a cardiac structure localization problem with convolutional architectures for aggregating global spatial context and detecting anatomical structures on spatial region proposals.
• This information is aggregated temporally by recurrent architectures to quantify the progressive motion patterns.