Recent Advances and Future Potential of Computer Aided Diagnosis of Liver Cancer on Computed Tomography Images

• Published in: Computer Networks and Intelligent Computing pp. 246 - 251
• Main Authors: Arakeri, Megha P., G., Ram Mohana Reddy
• Format: Book Chapter
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2011
• Series: Communications in Computer and Information Science
• Subjects: Computed Tomography; Computer Aided Diagnosis; Image Retrieval; Liver Cancer; Medical Imaging
• ISBN: 9783642227851; 3642227856
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-3-642-22786-8_31

Liver cancer has been known as one of the deadliest diseases. It has become a major health issue in the world over the past 30 years and its occurrence has increased in the recent years. Early detection is necessary to diagnose and cure liver cancer. Advances in medical imaging and image processing techniques have greatly enhanced interpretation of medical images. Computer aided diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver cancer and hence reduce death rate. The concept of computer aided diagnosis is to provide a computer output as a second opinion in analysis of liver cancer. It assists radiologist’s image interpretation by improving accuracy and consistency of radiological diagnosis and also by reducing image analysis time. The main objective of this paper is to provide an overview of recent advances in the development of CAD systems for analysis of liver cancer. Medical imaging system based on computer tomography will be focused as it is particularly suitable for detecting liver tumors. The paper begins with introduction to liver tumors and medical imaging techniques. Then the key CAD techniques developed recently for liver tumor detection, classification, case-based reasoning based on image retrieval and 3D reconstruction are presented. This article also explores the future key directions and highlights the research challenges that need to be addressed in the development of CAD system which can help the radiologist in improving the diagnostic accuracy.