Liver Tumour Detection through Artificial Intelligence: A Comprehensive Study

Liver tumours are a serious and life-threatening condition, which, if left untreated, can lead to fatal outcomes. Given the various challenges in early disease prediction, chronic impacts, and unbalanced diagnostic information, this study focuses on creating a comprehensive analysis of liver tumour segmentation techniques. It explores the roles of machine learning, deep learning, and neural networks in diversifying early detection frameworks. The study includes an examination of feature extraction techniques used in existing frameworks, emphasizing high-quality annotations. It also addresses the limitations of current datasets and the impact of real-time databases. Detailed insights into liver tumour segmentation methods are provided, highlighting the potential of artificial intelligence frameworks for future advancements. The primary goal of this system is to develop an efficient and robust framework for detecting, segmenting, and analysing liver tumours, with a key emphasis on early detection.