自动判断胎儿方位，辅助超声医生提高检查效率。
Determining Fetal Orientations From Blind Sweep Ultrasound Video
- 用模板匹配识别胎位，再分析脑部结构空间分布判断胎向。
- 在孕晚期数据集上准确率表现良好，可区分头位与臀位。
- 不替代医生，而是辅助提升产科超声操作流程效率。
胎儿超声检查对临床医生认知能力要求高，我们开发了一套自动化流程，仅需简单的盲扫超声视频即可预测胎儿方位。基于预训练的头部检测与分割模型，先通过模板匹配确定胎儿先露（头位或臀位），再根据分割出的脑部解剖结构空间分布判断胎向（左侧或右侧）。在孕晚期超声扫描数据集上的评估显示该方法具有较高准确性。本工作首次实现胎儿胎向的自动化预测，提出一种增强而非取代超声医师能力的辅助范式。未来研究将聚焦于提升采集效率，并探索实时临床集成，以优化工作流并支持产科医生。
原文摘要 · Abstract (English)
Cognitive demands of fetal ultrasound examinations pose unique challenges among clinicians. With the goal of providing an assistive tool, we developed an automated pipeline for predicting fetal orientation from ultrasound videos acquired following a simple blind sweep protocol. Leveraging on a pre-trained head detection and segmentation model, this is achieved by first determining the fetal presentation (cephalic or breech) with a template matching approach, followed by the fetal lie (facing left or right) by analyzing the spatial distribution of segmented brain anatomies. Evaluation on a dataset of third-trimester ultrasound scans demonstrated the promising accuracy of our pipeline. This work distinguishes itself by introducing automated fetal lie prediction and by proposing an assistive paradigm that augments sonographer expertise rather than replacing it. Future research will focus on enhancing acquisition efficiency, and exploring real-time clinical integration to improve workflow and support for obstetric clinicians.
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