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Artificial Intelligence and Computer Vision in Low Back Pain: A Systematic Review.
Federico D'Antoni1, Fabrizio Russo2, Luca Ambrosio2
1Unit of Computer Systems and Bioinformatics, Università Campus Bio-Medico di Roma, Via Alvaro Del Portillo 21, 00128 Rome, Italy.
International Journal of Environmental Research and Public Health
|October 23, 2021
Summary
Computer vision and artificial intelligence show promise in diagnosing and treating chronic low back pain (LBP). Advanced deep learning models achieve high accuracy in segmenting and identifying lumbar structures, improving LBP care.
Area of Science:
- Orthopaedics
- Medical Imaging
- Artificial Intelligence
Background:
- Chronic low back pain (LBP) is a leading global cause of disability.
- Advances in digital imaging within orthopaedics have spurred AI development.
- Computer vision offers potential for enhanced LBP diagnosis and treatment.
Purpose of the Study:
- To systematically review the literature on computer vision applications in LBP diagnosis and treatment.
- To identify current trends and performance metrics of AI-driven methods in lumbar imaging analysis.
Main Methods:
- Systematic literature search of the PubMed database.
- Keywords included: Artificial Intelligence, Computer Vision, Machine Learning, Deep Learning, Low Back Pain, Lumbar.
- Inclusion criteria based on abstract and full-text review, resulting in 76 eligible articles.
Main Results:
- Computer vision applications in LBP primarily involve feature extraction and segmentation.
- Deep learning models are increasingly preferred over traditional image processing techniques.
- High performance reported: >90% Sørensen-Dice for segmentation, >80% accuracy for localization/identification.
Conclusions:
- Computer vision, particularly deep learning, is a powerful tool for analyzing lumbar images in LBP.
- AI is enhancing the accuracy and reliability of diagnostic and treatment tools for LBP.
- Future AI advancements are expected to further improve system autonomy and effectiveness in managing LBP.
