UADSN: Uncertainty-Aware Dual-Stream Network for Facial Nerve Segmentation
- URL: http://arxiv.org/abs/2407.00297v1
- Date: Sat, 29 Jun 2024 03:30:29 GMT
- Title: UADSN: Uncertainty-Aware Dual-Stream Network for Facial Nerve Segmentation
- Authors: Guanghao Zhu, Lin Liu, Jing Zhang, Xiaohui Du, Ruqian Hao, Juanxiu Liu,
- Abstract summary: 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.
We propose an uncertainty-aware dualstream network (UADSN)
- Score: 13.928053592108267
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: 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.
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