Effective Methods to Detect Liver Cancer Using CNN and Deep Learning Algorithms

Abstract

Deaths from liver cancer are considerable. time- consuming manual cancer tissue detection. Hence, a computer- aided diagnostic (CAD) aids in selecting the proper course of action. Mammography, histology, MRI, ultrasound, and tomog- raphy images are the most accurate ways to find cancerous tissue. In medical imaging, CNNs, and deep learning enhance tumor identification and categorization. This study uses a CNN classifier with a cutting-edge methodology to accurately identify liver cancer. With the growth of deep learning, medical image analysis has become an important area of study. Typically, Medical Image Analysis refers to the use of several Medical professionals may employ several imaging modalities and procedures to obtain pictures of the human body, which are then used for patient diagnosis and treatment. This study gives an overview of the many ways that DL approaches have been used to improve medical picture analysis for different identification purposes.