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.