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Abstract #2308

Optimized U-net++: Novel Algorithm for Sub-regional Segmentation of KneeĀ  Cartilage and Bone

Lijie Zhong1, Jiaping Hu1, Shaolong Chen2, Yanjun Chen1, Zhongping Zhang3, Yingjie Mei3, Zhiyong Zhang2, and Xiaodong Zhang1
1Department of Medical Imaging, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China, 2School of Electronics and Communication Engineering, Sun Yat-sen University, Shenzhen, China, 3China International Center, Philips Healthcare, Guangzhou, China


Cartilage degeneration and subchondral bone alterations play an important role in the pathogenesis and progression of knee osteoarthritis (OA). MRI can detect morphological or compositional change of cartilage and bone. Regional analysis of cartilage and bone lesions would significantly improve the diagnosis of OA and help to understand its role in OA. Automated segmentation of cartilage and bone on MRI is a necessary first step for quantitative measures. Therefore, we proposed an optimized U-net (PSA-U-net++) to solve the problem of sub-regional segmentation of bone and cartilage. The initiatory results showed that our model can accurately segment cartilage and bone.

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