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Research progress of artificial intelligence in bone tumor imaging.

Wenwei Zhang1, Siwen Kang2, Keda Li2

  • 1Liaoning University of Traditional Chinese Medicine, Shenyang, China.

Frontiers in Oncology
|March 27, 2026
PubMed
Summary

Artificial intelligence (AI), especially deep learning (DL), enhances bone tumor imaging analysis for improved diagnosis and treatment. AI applications in radiology aid in accurate tumor recognition, classification, and efficacy assessment, benefiting patient outcomes.

Keywords:
artificial intelligencebone tumorsdeep learningimagingtreatment assessment

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Area of Science:

  • Radiology
  • Oncology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Bone tumors, both primary and metastatic, present diagnostic challenges due to rarity and varied imaging features.
  • Misdiagnosis of bone tumors significantly impacts patient prognosis and treatment effectiveness.

Purpose of the Study:

  • To review research progress on artificial intelligence (AI) in bone tumor imaging.
  • To explore AI's potential in enhancing diagnostic accuracy and clinical management of bone tumors.

Main Methods:

  • Review of current research on AI applications in bone tumor imaging.
  • Focus on deep learning (DL) algorithms for image recognition, segmentation, and classification.

Main Results:

  • AI, particularly DL, demonstrates effectiveness in automatic recognition and segmentation of bone tumor regions.
  • AI improves radiological image analysis efficiency and accuracy.
  • AI supports bone tumor classification and treatment efficacy assessment.

Conclusions:

  • AI shows significant potential to improve diagnostic accuracy and clinical management of bone tumors.
  • Future research should expand AI applications to diverse bone tumors and integrate multimodal imaging data for robust clinical decision-making.