Automated segmentation of abdominal organs from contrast-enhanced computed tomography using analysis of texture features

Generation of three-dimensional personalized geometric models of anatomical structures is an important process for many practical tasks: computer-aided diagnosis, treatment planning and numerical modeling in biomedical applications. Despite many efforts done by different research groups, automatic segmentation of organs still does not have any general solution. The main difficulties are caused by peculiarities of different medical imaging modalities, image variability (for the same modality) resulting from the wide range of imaging devices, noise and artifacts, large patient anatomical variability and overlapping of intensity ranges of neighboring anatomical structures. In this article, we propose segmentation method based on analysis of texture features and developed specially for segmentation of abdominal organs. Its main advantage is robustness to interpatient gray level and anatomical variability. The proposed method was validated on the patient data. The method implementation was accelerated using graphics processing unit (GPU).