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Effusion Area Segmentation for Knee Joint Ultrasound Image Based on Atrous-Fcn with Snake Model Algorithm

Knee synovitis is a common clinical disease with the increasing of knee joint effusion in symptom. The effusion area detected by ultrasonic signal is similar to the image background, which lead to false identification. To segment accurately the effusion area of the knee joint ultrasound image in our paper, Snake model algorithm and deep network are proposed to identify the effusion area, which can increase the MIoU by 10% after incorporating the Snake model algorithm. By atrous-FCN in this deep network, the balance between ‘small field of vision, and ‘big field of vision’ is found during selecting the number of atrous layers. Finally, MIoU can reach about 0.801 on the testing dataset, with accuracy of about 0.96.