Advancements in Communication and Systems
Review on Liver Cancer Detection using Deep Learning
Authors: Samrudhi Kore, Komal Ghare, Nishant Pol and Uma Patil
Publishing Date: 28-06-2024
ISBN: 978-81-955020-7-3
Abstract
The largest internal organ in the human body is the liver [1]. Cancer is the irregular growth of the tissue in an organ[3].In cancer, cells divide and proliferate erratically, creating dangerous tumors that spread to neighboring bodily parts[5].One kind of cancer that affects the largest organ in the abdomen is liver cancer. Liver cancer is one of the most prevalent illnesses and a leading cause of mortality in the world each year. Hepatocellular carcinoma (HCC), in particular, is a major cause of cancer-related deaths worldwide and necessitates the use of sophisticated and efficient diagnostic techniques for early identification. This article offers a thorough analysis of current developments in deep learning-based liver cancer detection. Deep learning, a subset of artificial intelligence, has shown promise in a variety of medical imaging applications, including the identification and detection of liver cancer. The review commences by delineating present obstacles in the diagnosis of liver cancer and stressing the significance of timely detection for enhanced patient consequences. An overview of deep learning techniques, including hybrid architectures, recurrent neural networks (RNN), and convolutional neural networks (CNN), is then provided. These deep learning models have demonstrated remarkable proficiency in terms of interpreting complex patterns and features from medical imaging data, particularly from computed tomography (CT) and magnetic resonance imaging (MRI) scans. The overview of the many states of cancer detection technologies is provided in this document, along with a discussion of each method's evaluation.
Keywords
Liver Cancer Detection, Machine Learning, Deep Learning, Image segmentation.
Cite as
Samrudhi Kore, Komal Ghare, Nishant Pol and Uma Patil, "Review on Liver Cancer Detection using Deep Learning", In: Ashish Kumar Tripathi and Vivek Shrivastava (eds), Advancements in Communication and Systems, SCRS, India, 2024, pp. 501-508. https://doi.org/10.56155/978-81-955020-7-3-44