Abstract #2308

Optimized U-net++: Novel Algorithm for Sub-regional Segmentation of Knee 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

Synopsis

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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