Due to that reading Automated 3D Breast Ultrasound (ABUS) images is time consuming,and subtle abnormalities may be missed.To make reading more efficient and to reduce reading errors,a computer-aided detection and evaluation algorithm is proposed to automatically find implanted lightweight meshes in ABUS images.First,a textural feature extraction algorithm is presented to automatically find candidate objects in the volume of interest and compute textural features on multiplanar images for classification of the mesh and fascia.Second,the 2D texture is more sensitive to the mesh shrinkage.Therefore,3D texture and 3D position parameters are introduced to enhance the robustness of the implanted meshes recognition method.Finally,the distance between class algorithm and a sequential forward selection algorithm are used for the feature selection And the support vector machine is used to classify and distinguish.The algorithm can effectively reduce the intensity of reading,and assists the doctor to identify the presence of lightweight patch in the ABUS scanning area.And it can assist in the evaluation of patch-related diagnostic programs.