Automatic evaluation of steatosis by ultrasound image analysis

This paper presents a new method for computer based diagnosis in liver steatosis diagnosis. The effectiveness of several image features extracted by robust estimation in conjunction with a random forests classifier for steatosis stage assessment is proved. We found that a successive dichotomy approach using random forests leads to better diagnosis than simultaneous classification with random forests.