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[Artificial intelligence in breast imaging : Hopes and challenges]
Matthias Dietzel1, Alexandra Resch2, Pascal A T Baltzer3
1Department of Radiology, University Hospital Erlangen, Erlangen, Deutschland.
Clinical/Methodical Issue:
Artificial intelligence (AI) is being increasingly integrated into clinical practice. However, the specific benefits are still unclear to many users.
Standard Radiological Methods:
In principle, AI applications are available for all imaging modalities, with a particular focus on mammography in breast diagnostics.
Methodical Innovations:
AI promises to filter examinations into negative and clearly positive findings, and thereby reduces part of the radiological workload. Other applications are not yet as widely established.
Performance:
AI methods for mammography, and to a lesser extent tomosynthesis, have already reached the diagnostic quality of radiologists.
Achievements:
Except for second-opinion applications/triage in mammography, most methods are still under development.
Practical Recommendations:
Currently, most AI applications must be critically evaluated by potential users regarding their maturity and practical benefits.
