Adaptive abdominal fat and liver segmentation of ct scan images for abdominal fat-fatty liver correlation

Overweight and obesity have become a major health concern in the world. Experts believe that fat accumulation in human body (especially at the abdominal zone) has a direct correlation with nonalcoholic fatty liver diseases. Nevertheless, there are no studies that highlight the relationship between a realistic representation of the quantity of abdominal fat and the level of diffused fat in the liver. This study aims to investigate the strength and the type of correlation between the indexes of abdominal fat and the level of diffused fat in human liver. Adaptive methods for abdominal fat segmentation and human liver segmentation using CT images are proposed. A modified Fuzzy C mean clustering method and Otsu thresholding technique are employed to segment the CT images of each subject into fat and non-fat tissues individually. Then, the segmented fat tissues in each CT slice are further separated into subcutaneous fat and visceral fat. Finally, the segmented fat tissues in the CT dataset for each subject are used to evaluate the quantities of abdominal fat by dividing the number of fat pixels over the number of total abdominal pixels. The whole liver segmentation procedure is based on processing the CT slices one by one. Gray level, Gaussian gradient, region growing algorithm,distance transformation, canny edge detector and anatomic information are employed together to segment the liver in each CT slice. Then the diffused fat in the segmented liver is evaluated by calculating the mean of liver attenuation (measured in Hounsfield Units) for the segmented liver. The lower the mean value, the lower the tissue density and hence the greater the fat content. Experimental results show that the performances of the abdominal fat segmentation method and the liver segmentation method are very promising. The abdominal fat segmentation method shows a great capability to handle a wide variety of abdominal wall shapes. The liver segmentation method also shows a good performance as well. Several challenges and difficulties due to the similarity of gray level intensities of the liver and the attached organs have been overcome in the proposed liver segmentation method. Data sets of 125 subjects were employed to study the relationship between abdominal fat accumulation and diffused fat in the liver. Experimental results show that there is medium negative correlation between the visceral fat to abdomen size ratio and the mean of liver intensity values (R= - 0.3168, P<0.0005). The same correlation is found between the mean of liver intensity values and the total abdominal fat to abdomen size ratio (R= - 0.3382, P<0.0005). In conclusion, it could be said that the accumulation of abdominal fat is not the main reason for the increase in the level of diffused fat in the liver. However it does somehow contribute towards the process of increasing that level.

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