Deep learning for predicting future lesion emergence in high-risk breast MRI screening: a feasibility study.
Bianca BurgerMaria BernathovaPhilipp SeeböckChristian F SingerThomas H HelbichGeorg LangsPublished in: European radiology experimental (2023)
• Breast lesions are associated with preceding anomalies in CE-MRI of high-risk women. • Deep learning-based anomaly detection can help to adjust risk assessment for future lesions. • An appearance anomaly score may be used for adjusting screening interval times.
Keyphrases
- deep learning
- risk assessment
- contrast enhanced
- magnetic resonance imaging
- current status
- artificial intelligence
- convolutional neural network
- diffusion weighted imaging
- polycystic ovary syndrome
- machine learning
- magnetic resonance
- metabolic syndrome
- type diabetes
- loop mediated isothermal amplification
- label free
- insulin resistance
- cervical cancer screening