Automatic Detection of Post-Operative Clips in Mammography Using a U-Net Convolutional Neural Network.
Tician SchnitzlerCarlotta RuppertPatryk HejdukKarol BorkowskiJonas KajüterCristina RossiAlexander CiritsisAnna LandsmannHasan ZaytounAndreas BossSebastian SchinderaFelice BurnPublished in: Journal of imaging (2024)
With this study, we show that surgery clips can adequately be identified by an AI technique. A potential application of the proposed technique is patient triage as well as the automatic exclusion of post-operative cases from PGMI (Perfect, Good, Moderate, Inadequate) evaluation, thus improving the quality management workflow.
Keyphrases
- deep learning
- convolutional neural network
- artificial intelligence
- machine learning
- emergency department
- minimally invasive
- case report
- high intensity
- loop mediated isothermal amplification
- quality improvement
- computed tomography
- magnetic resonance
- risk assessment
- electronic health record
- acute coronary syndrome
- label free
- coronary artery disease
- atrial fibrillation
- real time pcr