软件导刊2026，Vol.25Issue(4)：213-220,8.DOI:10.11907/rjdk.251571
基于深度学习的肾上腺CT图像分割研究综述
A Review of Deep Learning-Based Adrenal CT Image Segmentation Research
摘要
Abstract
Adrenal glands are tiny endocrine organs that play an important role in controlling blood pressure,heart rate,and other activities regulated by the sympathetic nervous system,and adrenal CT image segmentation is one of the key technologies in the intelligent diagnosis of adrenal-related diseases.In recent years,deep learning methods have played an important role in the automatic segmentation of adrenal CT images,which has driven the continuous progress in this field.In this paper,we systematically summarize the image preprocessing strategies,convolutional neural network and Transformer,and other deep learning models commonly used in existing research,and sort out the current re-search status of adrenal segmentation based on deep learning in the diagnosis of adrenal-related diseases.Finally,the future development di-rection of adrenal CT image segmentation in terms of dataset construction,model optimization and multi-task joint analysis is discussed,aim-ing to provide references for related research and clinical applications.关键词
CT图像/肾上腺/深度学习/图像分割/卷积神经网络Key words
CT image/adrenal gland/deep learning/image segmentation/convolutional neural network分类
信息技术与安全科学引用本文复制引用
房子洋,王津梁,肖裴垚,李轶凯,张治..基于深度学习的肾上腺CT图像分割研究综述[J].软件导刊,2026,25(4):213-220,8.基金项目
国家自然科学基金项目(82270536) （82270536）
