A textural features extraction algorithm for abdominal wall hernia mesh detection in automated 3D ultrasound images

A textural feature extraction algorithm was proposed to automatically find candidate objects in the selected volume of interest (VOI) and compute textural features on multiplanar images for classification of the mesh and fascia. Firstly, candidate objects were found out in axial plane (A-plane) and coronal plane (C-plane) images with the preprocessing stage. Secondly, textural features of candidate objects were extracted from the gray level co-occurrence matrix (GLCM). Finally, each feature extractor was evaluated using the criterion of distances between classes. Results demonstrated that the proposed algorithm can effectively detect the mesh and fascia in automated 3D ultrasound images. It can also provide significant textural features in the C-plane to distinguish between the mesh and fascia.