基因组学与应用生物学2024,Vol.43Issue(4) :708-718.DOI:10.13417/j.gab.043.000708

基于改进U-Net和X线片的脊柱侧弯Cobb角自动测量算法研究

Research on the Automatic Measurement Algorithm of Scoliosis Cobb Angle Based on Improved U-Net and X-Rays

禤浚波 梁英豪 梁淑慧 张绿云 胡巍 柯宝毅 马文宇 李成
基因组学与应用生物学2024,Vol.43Issue(4) :708-718.DOI:10.13417/j.gab.043.000708

基于改进U-Net和X线片的脊柱侧弯Cobb角自动测量算法研究

Research on the Automatic Measurement Algorithm of Scoliosis Cobb Angle Based on Improved U-Net and X-Rays

禤浚波 1梁英豪 2梁淑慧 3张绿云 4胡巍 5柯宝毅 6马文宇 6李成6
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作者信息

  • 1. 广西师范大学广西多源信息挖掘与安全重点实验室,桂林,541004;南宁职业技术学院人工智能学院,南宁,530008;广西师范大学计算机科学与工程学院,桂林,541004
  • 2. 南宁职业技术学院人工智能学院,南宁,530008
  • 3. 广西师范大学广西多源信息挖掘与安全重点实验室,桂林,541004;广西师范大学计算机科学与工程学院,桂林,541004
  • 4. 河池学院大数据与计算机学院,宜州,546300
  • 5. 桂林市人民医院脊柱骨病科,桂林,541002;柳州市人民医院脊柱外科,柳州,545006
  • 6. 桂林市人民医院脊柱骨病科,桂林,541002
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摘要

脊柱侧弯是影响人类健康的疾病之一,Cobb角的准确计算是临床上确定脊柱侧弯分型和制定诊疗方案的关键.针对人工测量Cobb角存在耗时长、不够准确、效率低下等问题,本文设计了一种基于改进U-Net的脊柱侧弯Cobb角 自动测量方法.由经验丰富的脊柱外科医生使用LabelMe工具对200例脊柱侧弯患者的X线片数据集进行标注.采用ResNet5 0作为主干网络改进基本的语义分割模型U-Net,并与另外2个语义分割模型DeeplabV3和PSPNet在脊柱侧弯X线片数据集上分别进行训练.实验结果表明,改进的U-Net模型的平均交并比(mean intersection over union,MIOU)值达到了94.72%,分别比PSPNet和DeeplabV3模型的MIOU值提升了5.36%和2.30%.最后,基于改进的U-Net模型设计了脊柱侧弯Cobb角的自动测量算法,并开发了可视化的自动测量软件.经过实际测试,发现在常规的电脑上输入一张患者的X线片,只需6.3 s即可自动计算Cobb角大小,其速度远快于医生手动测量,显著提高了医生的工作效率,表明本文设计的脊柱侧弯Cobb角 自动测量方法是有效的.

Abstract

Scoliosis is one of the diseases that affect human health.The accurate calculation of Cobb angle is the key to determine the classification of scoliosis and make the diagnosis and treatment plan.In order to solve the problems of time-consuming,inaccuracy and low efficiency in the manual measurement of Cobb angle,an automatic measurement method of scoliosis Cobb angle based on improved U-Net was designed in this paper.The X-ray data sets of 200 scoliosis patients were first annotated by an experienced spine surgeon using the LabelMe tool,and then the basic semantic segmentation model U-Net was improved using ResNet50 as the backbone network.The three semantic segmentation models that improved U-Net,DeeplabV3 and PSPNet,were designed and trained on the scoliosis X-ray data sets.The experimental results showed that the improved U-Net model achieved 94.72%in the mean intersection over union(MIOU)in-dex,which was better than PSPNet and DeeplabV3 models by 5.36%and 2.30%respectively.Finally.an automatic measurement algo-rithm of the Cobb angle of scoliosis based on the improved U-Net model was designed,and a visual automatic measurement software was developed.In the actual test,when inputing a patient's X-ray to a common computer,the software could automatically calculate the Cobb angle size only 6.3 s,which was much faster than doctors manual measurement,so this method can significantly improve the efficiency of the doctors.The test results showed that the designed automatic measurement method of the Cobb angle of scoliosis is effective.

关键词

脊柱侧弯/X线图像/Cobb角/U-Net/交并比

Key words

Scoliosis/X-ray images/Cobb angle/U-Net/Intersection over union

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基金项目

广西多源信息挖掘与安全重点实验室开放基金(MIMS21-02)

广西自然科学基金(2022GXNSFAA035625)

广西壮族自治区高等学校中青年教师科研基础能力提升项目(2022KY1019)

桂林市科学研究与技术开发计划(20210227-2)

广西卫生健康委科研项目(Z20210639)

出版年

2024
基因组学与应用生物学
广西大学

基因组学与应用生物学

CSTPCDCSCD北大核心
影响因子:1.108
ISSN:1674-568X
参考文献量19
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