A novel dual-branch segmentation algorithm for overall spine segmentation.

ABSTRACT:

Background

Accurate identification of bone structures helps surgeons to better locate target areas during the procedure and reduce damage to surrounding tissue. To efficiently automate the laborious task of labeling vertebrae in computed tomography (CT) images, we propose a DBU-Net deep learning segmentation network built upon the nnUnet framework.

Methods

Specifically, DBU-Net incorporates the multi-scale feature channel attention module and the dual-branch decoder architecture. The multi-scale feature channel attention module effectively combines image features from adjacent stages, integrating detailed and structural information from different scales. By applying a weighted operation, it adaptively adjusts the importance of each channel, enabling precise extraction of mul

SUBMITTER: Gao T 

PROVIDER: S-EPMC11994511 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature