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基于深度神经网络的增强CT图像肾脏分割模型的建立

罗辉 李培

重庆医学2025,Vol.54Issue(3):630-634,5.
重庆医学2025,Vol.54Issue(3):630-634,5.DOI:10.3969/j.issn.1671-8348.2025.03.013

基于深度神经网络的增强CT图像肾脏分割模型的建立

Establishment of a renal cortex and medulla segmentation model in X-ray computed tomography images based on deep neural networks

罗辉 1李培1

作者信息

  • 1. 宁波市鄞州区第二医院影像科,浙江 宁波 315000
  • 折叠

摘要

Abstract

Objective To construct an automatic kidney segmentation model based on deep neural net-work on enhanced CT images.Methods The renal arterial phase images of 64 patients with chronic kidney disease(CKD)were collected from January 2019 to October 2022.According to blood creatinine estimation of glomerular filtration rate(eGFR),they were divided into the mild renal injury group,the moderate renal inju-ry group,the severe renal injury group and the control group,16 in each group.ITK-Snap software was used to outline the images layer by layer,and the areas outlined were renal parenchyma and renal cortex.The data set was randomly divided into training sets and test sets,including 40 training sets(10 in each group)and 24 test sets(6 in each group).Segmentation models of renal parenchyma and cortex were obtained and verified.The quantification results of renal parenchymal volume and cortical volume segmentation were compared.Four groups of image test sets were compared with the Dice values of the model to discuss the quantitative evalua-tion of kidney and renal cortex volume with this model,and evaluate its accuracy.Results The results of quantification of renal parenchymal volume and cortical volume segmentation performance by enhanced CT kidney segmentation model based on deep neural network showed that the Dice value of renal parenchyma was 93.53%and that of renal cortex was 81.48%.There was no significant difference in Dice values of renal parenchy-mal volume and renal cortex volume among all the groups(F=3.467,4.972,P>0.05).Conclusion The en-hanced CT image kidney segmentation model based on deep neural network established can be used to seg-ment kidney parenchyma and cortex,and the obtained data are reliable.

关键词

计算机断层扫描/肾小球滤过率/肾皮质容积/肾实质容积

Key words

computed tomography/glomerular filtration rate/kidney cortex volume/kidney medulla volume

分类

医药卫生

引用本文复制引用

罗辉,李培..基于深度神经网络的增强CT图像肾脏分割模型的建立[J].重庆医学,2025,54(3):630-634,5.

基金项目

2024年度浙江省基础公益研究计划项目(LY24H160002) (LY24H160002)

2020年浙江省医药卫生科技计划项目(2020KY896). (2020KY896)

重庆医学

1671-8348

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