Abstract #2665

Fully Automatic Multi-label Segmentation of Knee joint MRI using Deep Learning Neural Networks

Siyue Li¹, Xiaorui Xu¹, Chun Ki Franklin Au², and Weitian Chen¹

¹CUHK lab of AI in radiology (CLAIR), Department of imaging and interventional radiology , The Chinese university of Hong Kong, HongKong, Hong Kong, ²Department of imaging and interventional radiology, The Chinese university of Hong Kong, Hong Kong, Hong Kong

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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