A textural features extraction algorithm for abdominal wall hernia mesh detection in automated 3D ultrasound images
- Resource Type
- Conference
- Authors
- Wu, Jun; Wang, Yuanyuan; Yu, Jinhua; Chen, Yue; Pang, Yun; Fan, Huaiyu; Qiu, Zhiying
- Source
- 2014 International Conference on Audio, Language and Image Processing Audio, Language and Image Processing (ICALIP), 2014 International Conference on. :48-52 Jul, 2014
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Signal Processing and Analysis
Ultrasonic imaging
Feature extraction
Three-dimensional displays
Breast
Fascia
Medical diagnostic imaging
abdominal wall hernia mesh
automated 3D ultrasound
coronal plane
co-occurrence matrix
- Language
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.