MINI REVIEW article
Front. Oncol.
Sec. Surgical Oncology
Research Progress of Artificial Intelligence in Bone Tumor Imaging
Wenwei Zhang 1
Siwen Kang 2
Keda Li 2
1. Liaoning University of Traditional Chinese Medicine, Shenyang, China
2. Liaoning University of Traditional Chinese Medicine Affiliated Hospital, Shenyang, China
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Abstract
Abstract:This paper reviews the research progress of artificial intelligence (AI) in bone tumor imaging and explores its potential applications in improving diagnostic accuracy and clinical management. Bone tumors, including primary and metastatic tumors, often face the risk of misdiagnosis due to their rarity and diverse imaging characteristics, which significantly impacts patient prognosis. AI technologies, particularly deep learning (DL) algorithms, have been widely applied to the automatic recognition and segmentation of bone tumor regions in images, enhancing the efficiency and accuracy of radiological image analysis. Furthermore, AI plays a crucial role in the classification of bone tumors and the assessment of treatment efficacy, providing support for the development of individualized treatment plans. With the continuous advancement of AI technology, future research should focus on expanding its applications across different types of bone tumors and integrating multimodal imaging data to further strengthen clinical decision-making and patient management.
Summary
Keywords
artificial intelligence, Bone tumors, deep learning, imaging, Treatment assessment
Received
04 January 2026
Accepted
19 February 2026
Copyright
© 2026 Zhang, Kang and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Keda Li
Disclaimer
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