Keywords: Rheumatoid Arthritis, DSC & DCE Perfusion The volume of synovitis change is one of the most important pathological features of rheumatoid arthritis. By quantitative analysis of the enhancement of synovitis, we can define the degree of the disease, and determine the treatment and diagnosis. Considering the time-consuming of manual outlining and visual assessment, this study uses machine learning methods to conduct quantitative analysis of TIC, and proposes an unsupervised learning method with excellent results, which is expected to be an alternative for the gold-standard manual synovitis contour outlining.
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