Analysis of diffuse parenchymal liver disease by liver scintigrams: Differential diagnosis using fuzzy inference and genetic algorithm in nuclear medicine

In nuclear medicine, diagnosis of diffuse parenchymal liver disease such as chronic hepatitis (CH) or liver cirrhosis (LC) is evaluated by size and distortion of the liver, distribution of radioactive tracer in the liver, size and activities of the tracer in the spleen, the degree of visualization of the bone marrow, etc, using colloid liver scintigraphy. It is not difficult to read a scintigram for a typical pattern; however in some cases it is difficult to distinguish between normal and CH or CH and LC visually. Therefore, we tried to use fuzzy inferences to perform differential diagnosis. Using fuzzy inference, differential diagnosis of LC could be performed up to 100%, but those of CH and Severe fibrosis (SF) could not be performed sufficiently. Therefore genetic algorithm was tried to determine the fuzzy rules. By combining genetic algorithm and fuzzy inference, CH, SF, and LC could be differentiated to the degree 70%, 60%, and 100%, respectively.