Attention-Gated Networks for Improving Ultrasound Scan Plane Detection

Understand

In this work, we apply an attention-gated network to real-time automated scan plane detection for fetal ultrasound screening.

• Scan plane detection in fetal ultrasound is a challenging problem due the poor image quality resulting in low interpretability for both clinicians and automated algorithms.
• To solve this, we propose incorporating self-gated soft-attention mechanisms.
• A soft-attention mechanism generates a gating signal that is end-to-end trainable, which allows the network to contextualise local information useful for prediction.