Identify the Severity of Cirrhosis Based on the Level of AST and ALT Enzymes Using Image Processing Approach and K-Means Clustering Method

The liver is an organ in the body that has an important and complex task for the continuity of all bodily functions. In daily life, the human body deals with ingredients that
have the potential to damage the liver, such as chemicals contained in the blood; as a result, the liver is susceptible to injury. In general, there are several diseases caused by viruses that can attack the liver, including Hepatitis, Hemochromatosis, Cirrhosis, Liver Cancer, Liver Abscess, and Impotence in the liver, but naturally, the liver can protect itself by regeneration. This paper presents a severity detection scheme for cirrhosis of the liver based on the Alanine Aminotransferase (ALT) and Aspartate Aminotransferase (AST) enzymes contained in the blood. Cirrhosis of the liver is a chronic liver disease characterized by damage to liver cells by connective tissues, followed by scarring and often accompanied by the formation of hundreds of nodules (lumps). This disease changes the structure of the liver from healthy liver tissue to abnormal hard bumps and changes in blood vessels. This system will assist medical experts and provide information to patients with liver cirrhosis to carry out further treatment based on predicting the state of a patient's
liver presented in 3D images. The limitations of this study only present a prediction of the state of a person's liver, which is indicated to suffer from cirrhosis of the liver based on the content of ALT and AST enzymes in the blood. The impact of this study is that it can assist in decision making and analysis to refer to more specific parts that deal with cases of liver
cirrhosis.

Keywords: Alanine Aminotransferase, Aspartate Aminotransferase, cirrhosis, image processing, K-Means clustering, liver.