Early Stage Liver Disease Prediction using Image Processing

Abstract

Abstract: Liver diseases have become increasingly common due to sedentary lifestyles and lack of physical activity, particularly in urban areas and metropolitan cities. This has resulted in millions of deaths every year, with liver cancer being a major contributor. However, inaccurate detection of liver tumors has led to many fatalities. Medical image segmentation is a challenging task when it comes to detecting liver tumors in CT images. Therefore, this project aims to improve the accuracy of tumor detection and segmentation using various image processing techniques, such as pre-processing, enhancement, and clustering algorithms. Early detection is critical in preventing liver cancer fatalities, and this project focuses on improving classification performance to aid in early detection. In this paper, we will describe the steps taken to select the best model and develop a necessary system for predicting liver disease.