Establishment of a renal cortex and medulla segmentation model in X-ray computed tomography images based on deep neural networks
10.3969/j.issn.1671-8348.2025.03.013
- VernacularTitle:基于深度神经网络的增强CT图像肾脏分割模型的建立
- Author:
Hui LUO
1
;
Pei LI
Author Information
1. 宁波市鄞州区第二医院影像科,浙江 宁波 315000
- Keywords:
computed tomography;
glomerular filtration rate;
kidney cortex volume;
kidney medulla volume
- From:
Chongqing Medicine
2025;54(3):630-634
- CountryChina
- Language:Chinese
-
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.
