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Fatty liver disease is progressive and may not cause any symptoms at early stages. This disease is potentially fatal and can cause liver cancer in severe stages. Therefore, diagnosing and staging fatty liver disease in early stages is necessary. In this paper, a novel method is presented to classify normal and fatty liver, as well as discriminate three stages of fatty liver in ultrasound images. This study is performed with 129 subjects including 28 normal, 47 steatosis, 42 fibrosis, and 12 cirrhosis images. The proposed approach uses back-scan conversion of ultrasound sector images and is based on a hierarchical classification. The proposed algorithm is performed in two parts. The first part selects the optimum regions of interest from the focal zone of the back-scan–converted ultrasound images. In the second part, discrimination between normal and fatty liver is performed and then steatosis, fibrosis, and cirrhosis are classified in a hierarchical basis. The wavelet packet transform and gray-level co-occurrence matrix are used to obtain a number of statistical features. A support vector machine classifier is used to discriminate between normal and fatty liver, and stage fatty cases. The results of the proposed scheme clearly illustrate the efficiency of this system with overall accuracy of 94.91% and also specificity of more than 90%.

IntroductionCervical spine, thoracic and pelvic fractures are the main causes of devastation in patients who have suffered blunt trauma. Radiographic imaging plays an important role in diagnosing such injuries. Nevertheless, the present dominant approach, the routine use of X-ray studies, seems to have no cost-benefit justification for healthcare systems.MethodsThis prospective cross-sectional study was performed over a 3-month period. During the determined time frame, all haemodynamically stable, high-energy blunt trauma patients were included. Based on the predefined criteria, selective radiographic images of the neck, chest and pelvis were obtained. Patients were followed during their hospital stay and for a 2-week period after discharge.Results1002 cases were included in the final survey. 247/1002 (24.6%) cervical radiographic images, 500/1002 (49.9%) CXRs and 171/1002 (17%) pelvic radiographic images of the patients were taken on the first day of hospital admission. New X-ray images required during the patients’ hospital stay resulted in 5/1002 (0.4%) cervical, 4/1002 (0.3%) chest and 8/1002 (0.7%) pelvic radiographies. In the 2-week period after discharge, 4/1002 cases (0.3%) needed to repeat neck radiography. Overall, 697.44 mSv X-ray radiation was potentially prevented and US$426 450 were potentially saved.ConclusionsSelective radiographic imaging of the neck, chest and pelvis together with a precise history-taking and physical examination in cases of high-energy blunt trauma could eliminate unnecessary costs to patients and healthcare systems, and significantly save resources.