Accurate segmentation of the cartilage and meniscus is highly desirable for diagnosis and treatment of knee joint diseases. We implemented and compared four deep learning neural networks for fully automated simultaneous segmentation of cartilage and meniscus. Using the Osteoarthritis Initiative (OAI) data sets, we demonstrated the U-net combined with specific post-processing achieved the best performance on femoral cartilage, tibial cartilage, patellar cartilage, and meniscus in terms of dice score.
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