UADSN: Uncertainty-Aware Dual-Stream Network for Facial Nerve Segmentation
<|reference_start|>UADSN: Uncertainty-Aware Dual-Stream Network for Facial Nerve Segmentation: Facial nerve segmentation is crucial for preoperative path planning in cochlear implantation surgery. Recently, researchers have proposed some segmentation methods, such as atlas-based and deep learning-based methods. However, since the facial nerve is a tubular organ with a diameter of only 1.0-1.5mm, it is challenging to locate and segment the facial nerve in CT scans. In this work, we propose an uncertainty-aware dualstream network (UADSN). UADSN consists of a 2D segmentation stream and a 3D segmentation stream. Predictions from two streams are used to identify uncertain regions, and a consistency loss is employed to supervise the segmentation of these regions. In addition, we introduce channel squeeze & spatial excitation modules into the skip connections of U-shaped networks to extract meaningful spatial information. In order to consider topologypreservation, a clDice loss is introduced into the supervised loss function. Experimental results on the facial nerve dataset demonstrate the effectiveness of UADSN and our submodules.<|reference_end|>
@article{zhu2024uadsn:,
    title={UADSN: Uncertainty-Aware Dual-Stream Network for Facial Nerve
  Segmentation},
    author={Guanghao Zhu and Lin Liu and Jing Zhang and Xiaohui Du and Ruqian Hao
  and Juanxiu Liu},
    journal={arXiv preprint arXiv:2407.00297},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.00297},
    primaryClass={eess.IV cs.CV}
}