兰州大学学报（医学版）2025，Vol.51Issue(7)：24-30,7.DOI:10.13885/j.issn.2097-681X.2025.07.004
深度学习应用于腋神经的超声图像识别
Application of deep learning in recognizing the axillary nerve on ultrasound images
摘要
Abstract
Objective To provide and validate a deep learning model for automatic axillary nerve segmentation to achieve automatically identify axillary nerve anatomy in real time.Methods The axillary nerve ultrasound images of 100 patients(54 males and 46 females)were retrospectively analyzed,and ITK-SNAP software was used to for manual labeling,and a dataset was established and divided into training and testing sets.A deep learning model for automatic axillary nerve segmentation was constructed based on the U-Mamba framework.Mean Intersection over Union(mIoU),mean Dice Similarity Coefficient(mDice)and accuracy rate were used to evaluate the performance of the model.Results A total of 831 ultrasound images were included to construct the entire dataset.Among them,683 ultrasound images were for training sets and 148 for for test sets.The to-tal mIoU and mDice coefficient of the training set were 0.980 and 0.990.The total mIoU of the test set was 0.672,the mDice coefficient was 0.776,and the segmentation accuracy was 99.3%.The median and upper and lower quartiles of the 5-fold cross-validated IoU were 0.981(0.978 to 0.983).Conclusion The model based on U-Mamba deep learning can achieve good results in the automatic identification of axillary nerve anatomy and has a good clinical application value.关键词
深度学习/U-Mamba/腋神经/超声/区域阻滞/自动分割/图像识别Key words
deep learning/U-Mamba/axillary nerve/ultrasound/regional anaesthesia/automatic segmenta-tion/image recognition分类
医药卫生引用本文复制引用
程偲,张明,黄生辉,胡万均..深度学习应用于腋神经的超声图像识别[J].兰州大学学报（医学版）,2025,51(7):24-30,7.基金项目
甘肃省自然科学基金资助项目(22JR5RA954) （22JR5RA954）
兰州市科技计划资助项目(2024-3-37) （2024-3-37）
