Getting Cartilage Thickness Measurements Right: A Systematic Inter-Method Comparison Using MRI Data from the Osteoarthritis Initiative.
Teresa LemainqueSimon WestfechtelJustus SchockMatthias KnobeTorsten PastorElisabeth PfaehlerChristiane KuhlDaniel TruhnSven NebelungPublished in: Cartilage (2023)
In automatic cartilage thickness determination, quantification accuracy and computational burden are largely affected by the underlying method. Mesh and surface normals or nearest neighbor searches should be used because they accurately capture variable geometries while being time-efficient.
Keyphrases
- optical coherence tomography
- extracellular matrix
- magnetic resonance imaging
- quality improvement
- contrast enhanced
- rheumatoid arthritis
- deep learning
- electronic health record
- machine learning
- knee osteoarthritis
- big data
- computed tomography
- risk factors
- solid phase extraction
- mass spectrometry
- diffusion weighted imaging
- simultaneous determination