[1]陈华元,吴勋,陈超敏,等.人工智能在肿瘤影像学诊断与分类上的应用[J].中国医学物理学杂志,2026,43(4):547-552.[doi:DOI:10.3969/j.issn.1005-202X.2026.04.019]
　CHEN Huayuan,WU Xun,CHEN Chaomin,et al.Applications of artificial intelligence in imaging diagnosis and classification of tumors[J].Chinese Journal of Medical Physics,2026,43(4):547-552.[doi:DOI:10.3969/j.issn.1005-202X.2026.04.019]
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人工智能在肿瘤影像学诊断与分类上的应用()

《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
43卷
期数:
2026年第4期
页码:
547-552
栏目:
医学人工智能
出版日期:
2026-04-28

文章信息/Info

Title:
Applications of artificial intelligence in imaging diagnosis and classification of tumors
文章编号:
1005-202X（2026）04-0547-06
作者:
陈华元1; 吴勋2; 陈超敏2; 冯丹茜3
1.广州南方医疗设备综合检测有限责任公司， 广东 广州510515； 2.南方医科大学生物医学工程学院， 广东 广州510515； 3.广东省医疗器械质量监督检验所， 广东 广州510663
Author(s):
CHEN Huayuan1;  WU Xun2;  CHEN Chaomin2;  FENG Danqian3
1. Guangzhou Southern Medical Equipment Comprehensive Testing Co., Ltd., Guangzhou 510515, China 2. School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China 3. Guangdong Medical Devices Quality Surveillance and Test Institute, Guangzhou 510663, China
关键词:
人工智能; 深度学习; 骨肿瘤; 脑肿瘤
Keywords:
Keywords: artificial intelligence deep learning bone tumor brain tumor
分类号:
R318
DOI:
DOI:10.3969/j.issn.1005-202X.2026.04.019
文献标志码:
A
摘要:
随着人工智能（AI）的发展，其在肿瘤诊断和分类方向所展现出的优势也越来越明显。本研究对AI在肿瘤影像学诊断与分类中的应用展开研究，重点探讨深度学习在骨肿瘤和脑肿瘤影像学诊断中的进展。首先，介绍AI和深度学习的基本概念及其在医学影像中的应用背景。详细阐述了AI在骨肿瘤影像学诊断中的应用，包括肿瘤检测、良恶性分类、转移性骨肿瘤诊断等方面，展示了深度学习模型在提高诊断准确性和效率方面的潜力。其次，讨论了AI在脑肿瘤分类中的应用，特别是卷积神经网络和深度残差网络在脑肿瘤MRI图像分类中的研究进展，表明AI在脑肿瘤分类中的表现与经验丰富的放射科医生相当，甚至更优。最后，总结AI在肿瘤影像学诊断中的优势与挑战，指出模型的可解释性、数据可获得性和泛化能力是未来研究的重要方向。虽然AI在肿瘤影像学诊断中展现出广阔的应用前景，但仍需进一步研究以克服现有挑战。
Abstract:
Abstract: With the development of artificial intelligence (AI), its advantages in tumor diagnosis and classification are becoming increasingly pronounced. This review summarizes the applications of AI in imaging diagnosis and classification of tumors, with an emphasis on the recent advances of deep learning in the imaging diagnosis of bone tumors and brain tumors. To begin with, an introduction to the basic concepts of AI and deep learning and their application background in medical imaging is provided. The applications of AI in imaging diagnosis of bone tumors, including tumor detection, benign and malignant classification, and diagnosis of metastatic bone tumors are elaborated in details, demonstrating the potential of deep learning models in improving the diagnostic accuracy and efficiency. Furthermore, the application of AI in brain tumor classification is discussed, highlighting the progress in convolutional neural network and depth residual network for brain tumor MRI image classification, and the results show that AI achieves performance comparable to or even superior to experienced radiologists in brain tumor classification. Ultimately, the advantages and challenges of AI in tumor imaging diagnosis are analyzed, and it is pointed out that model interpretability, data availability, and generalization ability represent important research directions for future research. Although AI exhibits broad application prospects in tumor imaging diagnosis, further research is still required to address the existing challenges.

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备注/Memo

备注/Memo:
【收稿日期】2025-11-13 【基金项目】国家重点研发计划（2023YFC2414502） 【作者简介】陈华元，工程师，研究方向：医疗仪器检测、医学图像处理，E-mail: 415081161@qq.com 【通信作者】冯丹茜，高级工程师，研究方向：医疗仪器检测、医学人工智能，E-mail: 571611621@qq.com
更新日期/Last Update: 2026-04-29