Fusion and ANN based classification of liver focal lesions using phases in magnetic resonance imaging

Detecting and diagnosing the liver focal lesions have vital importance in planning the treatments of the patients. While there is no need to apply any treatment for benign lesions, medical treatments or surgical operations are necessary in case of existence of malign lesions. Pre-contrast, arterial, portal venous and delayed venous phases in magnetic resonance imaging help to make clear diagnosis through their different contrast material holding properties. In this study, magnetic resonance images belonging to 60 patients are classified as benign/malign by using multi-resolution analysis methods and artificial neural networks. In proposed system, the magnetic resonance images taken from four different phases for each patient are merged with three multi-resolution analyses based on fusion rules and classified by using artificial neural networks. The accuracy rate of the study is reached to 90%.