Sequence-aware Pre-training for Echocardiography Probe Guidance
<|reference_start|>Sequence-aware Pre-training for Echocardiography Probe Guidance: Cardiac ultrasound probe guidance aims to help novices adjust the 6-DOF probe pose to obtain high-quality sectional images. Cardiac ultrasound faces two major challenges: (1) the inherently complex structure of the heart, and (2) significant individual variations. Previous works have only learned the population-averaged 2D and 3D structures of the heart rather than personalized cardiac structural features, leading to a performance bottleneck. Clinically, we observed that sonographers adjust their understanding of a patient's cardiac structure based on prior scanning sequences, thereby modifying their scanning strategies. Inspired by this, we propose a sequence-aware self-supervised pre-training method. Specifically, our approach learns personalized 2D and 3D cardiac structural features by predicting the masked-out images and actions in a scanning sequence. We hypothesize that if the model can predict the missing content it has acquired a good understanding of the personalized cardiac structure. In the downstream probe guidance task, we also introduced a sequence modeling approach that models individual cardiac structural information based on the images and actions from historical scan data, enabling more accurate navigation decisions. Experiments on a large-scale dataset with 1.36 million samples demonstrated that our proposed sequence-aware paradigm can significantly reduce navigation errors, with translation errors decreasing by 15.90% to 36.87% and rotation errors decreasing by 11.13% to 20.77%, compared to state-of-the-art methods.<|reference_end|>
@article{jiang2024sequence-aware,
    title={Sequence-aware Pre-training for Echocardiography Probe Guidance},
    author={Haojun Jiang, Zhenguo Sun, Yu Sun, Ning Jia, Meng Li, Shaqi Luo, Shiji
  Song, Gao Huang},
    journal={arXiv preprint arXiv:2408.15026},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.15026},
    primaryClass={cs.CV cs.AI}
}