Image quality and metal artifact reduction in total hip arthroplasty CT: deep learning-based algorithm versus virtual monoenergetic imaging and orthopedic metal artifact reduction.
Mark SellesRuud H H WellenbergDerk J SlotmanIngrid M NijholtJochen A C van OschKees F van DijkeMario MaasMartijn F BoomsmaPublished in: European radiology experimental (2024)
• Metal artifacts introduced by total hip arthroplasty hamper radiologic assessment on CT. • A deep-learning algorithm (DL-MAR) was compared to dual-layer CT images with O-MAR. • DL-MAR showed best image quality and diagnostic confidence. • Highest contrast-to-noise ratios were observed on the DL-MAR images.
Keyphrases
- image quality
- deep learning
- total hip arthroplasty
- dual energy
- computed tomography
- convolutional neural network
- artificial intelligence
- machine learning
- magnetic resonance
- contrast enhanced
- magnetic resonance imaging
- positron emission tomography
- optical coherence tomography
- mass spectrometry
- fluorescence imaging
- neural network