基于深度学习的腰椎间盘突出症辅助诊断
Assisted Diagnosis of Lumbar Disc Herniation Based on Deep Learning
张新菊 1崔亚轩 1胥义 1付强2
作者信息
- 1. 上海理工大学 健康科学与工程学院,上海 200082
- 2. 上海理工大学 健康科学与工程学院,上海 200082;上海市第一人民医院 脊柱外科,上海 200080
- 折叠
摘要
针对腰椎骨结构复杂智能辅助诊断难的问题,提出一种基于深度学习的计算机辅助诊断方法框架,对腰椎间盘突出症(LDH)进行辅助诊断.首先,在U-Net的编码和解码过程中加入Resblock模块且保留U-Net的跳跃连接,以增强目标区域特征传递、减少特征丢失并加快模型收敛速度.其次,通过最小包络矩形法定位椎骨中心,根据定位在椎骨矢状面原图上裁剪合适大小的ROI,实现全自动ROI获取.最后,在Xception网络中使用平均池化代替Flatten操作,添加BN层、Droupout层和动态学习率提升模型的速度和精确度.针对上海某医院腰椎间盘突出症的MRI病例,通过分类模型评价标准评估训练后发现,所提框架诊断准确率ACC为94.46%,特异性SPE为94.60%,灵敏性SEN为97.09%,精确率PRE为94.32%,相较于以往研究均有提升,对推动计算机智能辅助诊断在临床上的应用具有重要意义.
Abstract
Aiming at the problem of difficulty in intelligent assisted diagnosis of complex lumbar spine bone structure,a deep learning based computer-aided diagnostic method framework is proposed to assist in the diagnosis of lumbar disc herniation(LDH).Firstly,a Resblock mod-ule is added to the encoding and decoding process of U-Net while preserving the skip connections of U-Net to enhance feature transfer in the target area,reduce feature loss,and accelerate model convergence speed.Secondly,the minimum envelope rectangle method is used to locate the center of the vertebrae,and ROI of appropriate size is cropped on the sagittal plane of the vertebrae based on the positioning,achieving ful-ly automatic ROI acquisition.Finally,in the Xception network,average pooling is used instead of Flatten operation,and BN layer,Droupout layer,and dynamic learning rate are added to improve the speed and accuracy of the model.Regarding the MRI case of lumbar disc herniation in a certain hospital in Shanghai,after evaluating and training the classification model evaluation criteria,it was found that the proposed framework had a diagnostic accuracy of 94.46%for ACC,94.60%for specific SPE,97.09%for sensitivity SEN,and 94.32%for accuracy PRE.Compared with previous studies,this has been improved,which is of great significance for promoting the clinical application of comput-er-aided diagnosis.
关键词
深度学习/U-Net/腰椎间盘突出症诊断/Xception/椎骨分割/智能辅助诊断Key words
deep learning/U-Net/diagnosis of lumbar disc herniation/Xception/segmentation of vertebrae/intelligent aided diagnosis引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据