Artificial Intelligence in Veterinary Diagnostic Imaging: A Narrative Review of the State of the Art and its Applications.

AI significantly improves speed and accuracy of veterinary diagnostic imaging interpretation across modalities.

This narrative review examines the transformative role of artificial intelligence in veterinary diagnostic imaging across multiple modalities including MRI, CT, CBCT, ultrasound, and radiography. The authors systematically reviewed contemporary literature to assess AI applications in veterinary diagnostics, identifying target organs, diseases, and affected animal species. Dogs and mice emerged as the primary subjects of AI research in veterinary imaging. Notable achievements include superior performance in automated segmentation of MRI images and accurate classification of thoracic lesions and cardiac pathologies on radiographic studies. The review demonstrates that AI technologies substantially enhance diagnostic accuracy, interpretation speed, and workflow efficiency while addressing the growing shortage of veterinary radiologists. These intelligent systems have the potential to standardize diagnostic protocols and reduce interpretation variability across veterinary practices. While the field remains emerging, the evidence indicates substantial promise for expanded implementation across diverse veterinary clinical settings and imaging modalities.

This summary was distilled by AI and may occasionally misinterpret data. Confirm critical details with the primary literature before clinical application.