Computer Aided Diagnosis of Liver Diseases Using Ultrasound Images

Abstract

Liver is one of the most important organs in the human body, because it plays a vital role in digestion and in the metabolization of protein, drugs, toxins etc. Diseases of the liver are becoming major cause of morbidity and mortality all over the world. Ultrasound is preferable imaging modality by medical practitioners for the screening of liver diseases. It is preferable because of its several advantages; it is a non-invasive, cost effective, non-ionizing, portable and real time imaging modality. Medical practitioners/radiologists diagnose liver diseases by the visual examination of ultrasound images. Visual examination is a subjective criterion and is highly dependent on the expertise of radiologists in the domain. This may lead to ambiguity in the diagnostic procedure. To improve the objectivity in the diagnostics of liver diseases, various approaches of designing computer-aided support system are explored in this thesis. In addition, the visualization of liver diseases in ultrasound images becomes a tedious task due to overlapping textural characteristics of liver diseases. Thus, to design the computer-aided diagnostic (CAD) system, in-depth textural analysis of ultrasound images is performed to quantify information related to liver diseases. This research work is carried out with a database of 189 B-mode ultrasound images. The database was developed by collecting images from patients visiting Manipal Hospital, Bangalore, India during the period from March 2013 to August 2014. These patients were recommended for liver examination. In this duration of one year, ultrasound images were collected from 94 patients; among those 67 were male (age range: 21-70) and 27 were female (age range: 23-61). The database encompasses 48 images of normal liver and 141 images of abnormal liver. Images related to abnormal liver comprise of 50 images of chronic liver, 50 images of cirrhotic liver, and 41 images related to HCC evolved over cirrhosis. Diagnostically relevant areas in liver images are regions-of-interest (ROIs).